Mathematics of Data/Image Coding, Compression, and Encryption VI, with Applications, 2004
This paper describes data compression algorithms capable to preserve the scientific quality of re... more This paper describes data compression algorithms capable to preserve the scientific quality of remote-sensing data, yet allowing a considerable bandwidth reduction to be achieved. Unlike lossless techniques, by which a moderate a compression ratio (CR) is attainable, due to intrinsic noisiness of the data, and conventional lossy techniques, in which the mean squared error of the decoded data is globally
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003
Goal of this work is to investigate lossy compression method- ologies from the viewpoint of spect... more Goal of this work is to investigate lossy compression method- ologies from the viewpoint of spectral distortion introduced in hyperspec- tral pixel vectors, besides that of radiometric distortion. The main result of this analysis is that, for a given compression ratio, near-lossless methods, i.e., with constrained pixel error, either absolute or relative, are more suit- able for preserving the spectral
Geoscience and Remote Sensing IEEE International Symposium, 1997
A modified inter-band scheme based on the predictors used by lossless JPEG is proposed for lossle... more A modified inter-band scheme based on the predictors used by lossless JPEG is proposed for lossless data compression of multispectral images. Basically, the value of the current pixel in the current band is predicted by the best JPEG predictor on the previously encoded band. Improvements are achieved by considering also the corresponding prediction error on the previous band. Coding performances,
Goal of this work is to present a general and formal solution to the problem of synergetic integr... more Goal of this work is to present a general and formal solution to the problem of synergetic integration of multi-sensor image data, which may be collected with practically whatsoever spectral and ground resolution, although scale ratios larger than, say, , may be questionable in certain applicative contexts. The proposed data fusion methodology is applied to a specific example concerning observations from two different multi-spectral satellite sensors: Landsat TM ( resolution) and MOMS-2P ( ). The fusion procedure relies on the generalized Laplacian pyramid(GLP), which is a non-octave band-pass analysis structure unconstrained from the ground scales of the imaged data. The advantage is that the base-band extracted from the finer image exactly matches both in displaying scale and in resolution, i.e. content of spatial frequencies, the coarser image. For any rational scale ratio, a unique low-pass filter is needed. The filter design, however, is easy and noncritical for performances. T...
The work focuses on evaluating quality and estimating information of CHRIS hyper-spectral images.... more The work focuses on evaluating quality and estimating information of CHRIS hyper-spectral images. Quality is assessed through the characterisation of the noise while information is estimated by means of an operative def- inition according to which the information content of a data set is given by the amount of information that can- not be predicted from the data that have already been ac- quired and, thus, by the entropy of the prediction errors. The noise model is first verified and the parameters of the model are then estimated. Afterwards lossless data com- pression is exploited to measure the entropy of the predic- tion errors through their bit-rate. The information content of the data is estimated by taking into account that the bit-rate achieved by the reversible compression process is due to both the contribution of the noise, whose relevance is null to a user, and of the hypothetically noise-free data. Since our goal is to estimate the amount of information of the ideal nois...
This work presents a general and formal solution to the problem of fusion of multispectral data w... more This work presents a general and formal solution to the problem of fusion of multispectral data with high-resolution panchromatic images. The method relies on the generalized Laplacian pyramid, which is an oversampled structure obtained by subtracting from an image its lowpass version, and selectively performs spatial-frequencies spectrum substitution from one image to another. The novelty of the present work is that a decision based on thresholding the local CC is utilized to check the physical, congruence of fusion, while the ratio of local RMSs between the two images provides a space-varying gain factor by which the injected highpass contribution is equalized. Since the pyramid decomposition is not critically-subsampled, possible impairments in the fused images, due to missing cancellation of aliasing terms, are avoided. Quantitative results are presented and discussed on simulated SPOT 5 data of an urban area (2.5 m P, 10 m XS) obtained from the MIVIS airborne imaging spectrometer
The definition of noise models suitable for hyperspectral data is slightly different depending on... more The definition of noise models suitable for hyperspectral data is slightly different depending on whether whiskbroom or push-broom are dealt with. Focussing on the latter type (e.g., VIRS-200) the noise is intrinsically non-stationary in the raw digital counts. After calibration, i.e. removing the variability effects due to different gains and offsets of detectors, the noise will exhibit stationary statistics, at least spatially. Hence, separable 3D processes correlated across track (x), along track (y) and in the wavelength (?), modelled as auto-regressive with GG statistics have been found to be adequate. Estimation of model parameters from the true data is accomplished through robust techniques relying on linear regressions calculated on scatter-plots of local statistics. An original procedure was devised to detect areas within the scatter-plot corresponding to statistically homogeneous pixels. Results on VIRS-200 data show that the noise is heavy-tailed (tails longer than those ...
International Conference on Digital Signal Processing, 1997
A class of signal-dependent noise models is discussed, with reference to the cases of film-grain ... more A class of signal-dependent noise models is discussed, with reference to the cases of film-grain and speckle noise, which are commonly encountered in image processing applications. The model is uniquely defined by the variance of the zero-mean random noise (independent of the signal) and by the gamma exponent which rules the dependence with the signal. A robust procedure for measuring
2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011
ABSTRACT This paper shows that the signal dependent nature of the noise introduced by up to date ... more ABSTRACT This paper shows that the signal dependent nature of the noise introduced by up to date imaging spectrometers is crucial for the spectral analysis carried out by the maximum noise fraction (MNF) transformation, which requires a preliminary estimation, either supervised or not, of the covariance matrix of the noise. Once the parametric noise model of the instrument has been estimated with the aid of calibration panels placed within the imaged scene, the mixed noise, i.e. photonic + electronic, can be removed. Noise filtering provides negligible improvements in the signal to noise ratio (SNR), at least whenever SNR is sufficiently high, but allows a correct spectral analysis to be accomplished via the MNF transformation, also in the absence of calibration panels. Conversely, the unsupervised estimation of the covariance matrix of the signal dependent noise may introduce unpredictable gross errors in the calculation of MNF transformation, thereby leading to transformed components that do not adequately capture the energy of the hyperspectral data.
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
In this work, a simple preprocessing patch is intro- duced before the Gram-Schmidt (GS) spectral ... more In this work, a simple preprocessing patch is intro- duced before the Gram-Schmidt (GS) spectral sharpening method (as implemented in ENVI) such that the resulting fused multispec- tral (MS) data exhibit higher sharpness and spectral quality. This is achieved by defining a generalized intensity (GI) component as a weighted average of the MS bands, with weights taken either as percentages
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003
MULTIRESOLUTION APPROACHES TO ADAPTIVE SPECKLE REDUCTION IN SYNTHETICAPERTURE RADAR IMAGES ... ou... more MULTIRESOLUTION APPROACHES TO ADAPTIVE SPECKLE REDUCTION IN SYNTHETICAPERTURE RADAR IMAGES ... out on both simulated speckled images and true SAR images demonstrate that the ... The majority of despeckling filters rely on the multiplica-tive speckle ...
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003
This work presents a viable solution to the problem of merging a multispectral image with an arbi... more This work presents a viable solution to the problem of merging a multispectral image with an arbitrary number of bands with a higher resolution panchromatic observation. The proposed method relies on the generalized Laplacian pyramid, which is a multiscale oversampled structure in which spatial details are mapped on different scales. The goal is to selectively perform spatial-frequencies spectrum substitution from
Proceedings of 3rd IEEE International Conference on Image Processing, 1996
In this work, it is shown that the generalized recursive interpolation (GRINT) proposed is the mo... more In this work, it is shown that the generalized recursive interpolation (GRINT) proposed is the most effective progressive technique for inter-frame reversible compression of tomographic sections that typically occur in the medical field. An image sequence is decimated by a factor 2, first along rows only, then along columns only, and eventually along slices only, recursively in a sequel, thus creating a gray-level hyperpyramid whose number of voxels halves at every level. The top of the pyramid (root) is stored and then directionally interpolated by means of a 1D kernel. Interpolation errors with the underlying equally-sized hyperlayer are stored as well. The same procedure is repeated, until the image sequence is completely decomposed. The advantage of the novel scheme with respect to other noncausal DPCM schemes is twofold: firstly interpolation is performed from all error-free values, thereby reducing the variance of residuals; secondly different correlation values along rows, columns and sections can be exploited for a better decorrelation
2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009
This paper deals with an original method to estimate the noise introduced by optical imaging syst... more This paper deals with an original method to estimate the noise introduced by optical imaging systems, such as CCD cameras, multispectral scanners and imaging spectrometers. The power of the signal-dependent photonic noise is decoupled from the power of the signal-independent noise generated by the electronic circuitry. The method relies on the multivariate regression of local sample statistics such as mean and variance, in which statistically homogeneous pixels produce scatter-points that are clustered along a straight line, whose slope and intercept measure the signal-dependent and signal-independent components of the noise power, respectively. Experimental results carried out on a simulated noisy image and on true data from a modern generation airborne imaging spectrometer highlight the accuracy of the proposed method and its robustness to image textures that may lead to a gross overestimation of the noise, especially for high SNR.
Image and Signal Processing for Remote Sensing IV, 1998
ABSTRACT This paper reports about a quantitative evaluation of pyramid- based schemes performing ... more ABSTRACT This paper reports about a quantitative evaluation of pyramid- based schemes performing a feature-based fusion of data from multispectral and panchromatic imaging sensors having different ground resolutions. A critical point is performances evaluation of image data fusion. A set of quantitative parameters has been recently proposed. Both visual quality, regarded as contrast, presence of fine details, and absence of impairments and artifacts (e.g., blur, ringing), and spectral fidelity (i.e., preservation of spectral signatures) are concerned and embodied in the measurements. The aim of the present work is to provide a comprehensive performance comparison on SPOT data among three feature-based schemes for image fusion, as well as on a specific case study on which multisensor observations were available. Out of the three methods compared, respectively based on high-pass filtering (HPF), wavelet transform (WT), and generalized Laplacian pyramid (GLP), the latter two are far more efficient than the former, thus establishing the advantages for data fusion of a formally multiresolution analysis.
Proceedings of SPIE - The International Society for Optical Engineering
In this work, a multi-resolution procedure based on a generalized Laplacian pyramid (GLP), with p... more In this work, a multi-resolution procedure based on a generalized Laplacian pyramid (GLP), with p:q (i.e. rational) scale factor, is proposed to merge image data of any resolution and represent them at any scale. The GLP- based data fusion is shown to be slightly superior to those of a similar scheme based on the discrete wavelet transform (WT), according to a set of parameters established in the literature. Not only fused images look sharper than their original versions, but also textured regions are enhanced without losing their spectral signatures. The pyramid- generating filters can be easily designed for data of any resolutions, differently from the WT, whose filter-bank design is non-trivial when the ratio between the scales of the images to be merged is not a power of two. Eventually, remotely sensed images from LandSat TM and from Panchromatic SPOT are fused together. The resulting bands capture multi- spectral features with enhanced contrast and texture, and an increased sp...
Proceedings of SPIE - The International Society for Optical Engineering
Speckle reduction in synthetic aperture radar (SAR) images is a key point to facilitate applicati... more Speckle reduction in synthetic aperture radar (SAR) images is a key point to facilitate applicative tasks. A filter aimed at speckle reduction should energetically smooth homogeneous regions, while preserving point targets, edges, and linear features. A tradeoff, however, should be arranged on textured areas. Filtering capabilities depend on local image characteristics, and generally no filter outperforms the others in every situation. In this work, a set of adaptive filters is considered with attention to those oriented towards a multiresolution approach. Images are individually processed by each filter, and the output at each pixel position is obtained by choosing one out of the channels. The selection is based on thresholding local features accounting for both space-varying statistics and geometry. Results on true SAR images show that also an empirical choice of thresholds is noncritical: the novel scheme outperforms each filter individually, at least according to visual criteria.
Proceedings of SPIE - The International Society for Optical Engineering
Several attempts have been made to merge Landsat TM multispectral data with high spatial resoluti... more Several attempts have been made to merge Landsat TM multispectral data with high spatial resolution panchromatic SPOT images. In this work a multiresolution approach based on a generalized Laplacian pyramid with p:q (i.e., rational) scale factor is proposed to merge image data of any resolution and represent them at any scale. The resulting bands capture multispectral characteristics with an enhanced spatial resolution, thereby expediting visual analysis and contextual interpretation of the environment according to archaeological issues. Objective and subjective evaluations show the effectiveness of the proposed method.
Mathematics of Data/Image Coding, Compression, and Encryption VI, with Applications, 2004
This paper describes data compression algorithms capable to preserve the scientific quality of re... more This paper describes data compression algorithms capable to preserve the scientific quality of remote-sensing data, yet allowing a considerable bandwidth reduction to be achieved. Unlike lossless techniques, by which a moderate a compression ratio (CR) is attainable, due to intrinsic noisiness of the data, and conventional lossy techniques, in which the mean squared error of the decoded data is globally
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003
Goal of this work is to investigate lossy compression method- ologies from the viewpoint of spect... more Goal of this work is to investigate lossy compression method- ologies from the viewpoint of spectral distortion introduced in hyperspec- tral pixel vectors, besides that of radiometric distortion. The main result of this analysis is that, for a given compression ratio, near-lossless methods, i.e., with constrained pixel error, either absolute or relative, are more suit- able for preserving the spectral
Geoscience and Remote Sensing IEEE International Symposium, 1997
A modified inter-band scheme based on the predictors used by lossless JPEG is proposed for lossle... more A modified inter-band scheme based on the predictors used by lossless JPEG is proposed for lossless data compression of multispectral images. Basically, the value of the current pixel in the current band is predicted by the best JPEG predictor on the previously encoded band. Improvements are achieved by considering also the corresponding prediction error on the previous band. Coding performances,
Goal of this work is to present a general and formal solution to the problem of synergetic integr... more Goal of this work is to present a general and formal solution to the problem of synergetic integration of multi-sensor image data, which may be collected with practically whatsoever spectral and ground resolution, although scale ratios larger than, say, , may be questionable in certain applicative contexts. The proposed data fusion methodology is applied to a specific example concerning observations from two different multi-spectral satellite sensors: Landsat TM ( resolution) and MOMS-2P ( ). The fusion procedure relies on the generalized Laplacian pyramid(GLP), which is a non-octave band-pass analysis structure unconstrained from the ground scales of the imaged data. The advantage is that the base-band extracted from the finer image exactly matches both in displaying scale and in resolution, i.e. content of spatial frequencies, the coarser image. For any rational scale ratio, a unique low-pass filter is needed. The filter design, however, is easy and noncritical for performances. T...
The work focuses on evaluating quality and estimating information of CHRIS hyper-spectral images.... more The work focuses on evaluating quality and estimating information of CHRIS hyper-spectral images. Quality is assessed through the characterisation of the noise while information is estimated by means of an operative def- inition according to which the information content of a data set is given by the amount of information that can- not be predicted from the data that have already been ac- quired and, thus, by the entropy of the prediction errors. The noise model is first verified and the parameters of the model are then estimated. Afterwards lossless data com- pression is exploited to measure the entropy of the predic- tion errors through their bit-rate. The information content of the data is estimated by taking into account that the bit-rate achieved by the reversible compression process is due to both the contribution of the noise, whose relevance is null to a user, and of the hypothetically noise-free data. Since our goal is to estimate the amount of information of the ideal nois...
This work presents a general and formal solution to the problem of fusion of multispectral data w... more This work presents a general and formal solution to the problem of fusion of multispectral data with high-resolution panchromatic images. The method relies on the generalized Laplacian pyramid, which is an oversampled structure obtained by subtracting from an image its lowpass version, and selectively performs spatial-frequencies spectrum substitution from one image to another. The novelty of the present work is that a decision based on thresholding the local CC is utilized to check the physical, congruence of fusion, while the ratio of local RMSs between the two images provides a space-varying gain factor by which the injected highpass contribution is equalized. Since the pyramid decomposition is not critically-subsampled, possible impairments in the fused images, due to missing cancellation of aliasing terms, are avoided. Quantitative results are presented and discussed on simulated SPOT 5 data of an urban area (2.5 m P, 10 m XS) obtained from the MIVIS airborne imaging spectrometer
The definition of noise models suitable for hyperspectral data is slightly different depending on... more The definition of noise models suitable for hyperspectral data is slightly different depending on whether whiskbroom or push-broom are dealt with. Focussing on the latter type (e.g., VIRS-200) the noise is intrinsically non-stationary in the raw digital counts. After calibration, i.e. removing the variability effects due to different gains and offsets of detectors, the noise will exhibit stationary statistics, at least spatially. Hence, separable 3D processes correlated across track (x), along track (y) and in the wavelength (?), modelled as auto-regressive with GG statistics have been found to be adequate. Estimation of model parameters from the true data is accomplished through robust techniques relying on linear regressions calculated on scatter-plots of local statistics. An original procedure was devised to detect areas within the scatter-plot corresponding to statistically homogeneous pixels. Results on VIRS-200 data show that the noise is heavy-tailed (tails longer than those ...
International Conference on Digital Signal Processing, 1997
A class of signal-dependent noise models is discussed, with reference to the cases of film-grain ... more A class of signal-dependent noise models is discussed, with reference to the cases of film-grain and speckle noise, which are commonly encountered in image processing applications. The model is uniquely defined by the variance of the zero-mean random noise (independent of the signal) and by the gamma exponent which rules the dependence with the signal. A robust procedure for measuring
2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011
ABSTRACT This paper shows that the signal dependent nature of the noise introduced by up to date ... more ABSTRACT This paper shows that the signal dependent nature of the noise introduced by up to date imaging spectrometers is crucial for the spectral analysis carried out by the maximum noise fraction (MNF) transformation, which requires a preliminary estimation, either supervised or not, of the covariance matrix of the noise. Once the parametric noise model of the instrument has been estimated with the aid of calibration panels placed within the imaged scene, the mixed noise, i.e. photonic + electronic, can be removed. Noise filtering provides negligible improvements in the signal to noise ratio (SNR), at least whenever SNR is sufficiently high, but allows a correct spectral analysis to be accomplished via the MNF transformation, also in the absence of calibration panels. Conversely, the unsupervised estimation of the covariance matrix of the signal dependent noise may introduce unpredictable gross errors in the calculation of MNF transformation, thereby leading to transformed components that do not adequately capture the energy of the hyperspectral data.
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
In this work, a simple preprocessing patch is intro- duced before the Gram-Schmidt (GS) spectral ... more In this work, a simple preprocessing patch is intro- duced before the Gram-Schmidt (GS) spectral sharpening method (as implemented in ENVI) such that the resulting fused multispec- tral (MS) data exhibit higher sharpness and spectral quality. This is achieved by defining a generalized intensity (GI) component as a weighted average of the MS bands, with weights taken either as percentages
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003
MULTIRESOLUTION APPROACHES TO ADAPTIVE SPECKLE REDUCTION IN SYNTHETICAPERTURE RADAR IMAGES ... ou... more MULTIRESOLUTION APPROACHES TO ADAPTIVE SPECKLE REDUCTION IN SYNTHETICAPERTURE RADAR IMAGES ... out on both simulated speckled images and true SAR images demonstrate that the ... The majority of despeckling filters rely on the multiplica-tive speckle ...
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003
This work presents a viable solution to the problem of merging a multispectral image with an arbi... more This work presents a viable solution to the problem of merging a multispectral image with an arbitrary number of bands with a higher resolution panchromatic observation. The proposed method relies on the generalized Laplacian pyramid, which is a multiscale oversampled structure in which spatial details are mapped on different scales. The goal is to selectively perform spatial-frequencies spectrum substitution from
Proceedings of 3rd IEEE International Conference on Image Processing, 1996
In this work, it is shown that the generalized recursive interpolation (GRINT) proposed is the mo... more In this work, it is shown that the generalized recursive interpolation (GRINT) proposed is the most effective progressive technique for inter-frame reversible compression of tomographic sections that typically occur in the medical field. An image sequence is decimated by a factor 2, first along rows only, then along columns only, and eventually along slices only, recursively in a sequel, thus creating a gray-level hyperpyramid whose number of voxels halves at every level. The top of the pyramid (root) is stored and then directionally interpolated by means of a 1D kernel. Interpolation errors with the underlying equally-sized hyperlayer are stored as well. The same procedure is repeated, until the image sequence is completely decomposed. The advantage of the novel scheme with respect to other noncausal DPCM schemes is twofold: firstly interpolation is performed from all error-free values, thereby reducing the variance of residuals; secondly different correlation values along rows, columns and sections can be exploited for a better decorrelation
2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009
This paper deals with an original method to estimate the noise introduced by optical imaging syst... more This paper deals with an original method to estimate the noise introduced by optical imaging systems, such as CCD cameras, multispectral scanners and imaging spectrometers. The power of the signal-dependent photonic noise is decoupled from the power of the signal-independent noise generated by the electronic circuitry. The method relies on the multivariate regression of local sample statistics such as mean and variance, in which statistically homogeneous pixels produce scatter-points that are clustered along a straight line, whose slope and intercept measure the signal-dependent and signal-independent components of the noise power, respectively. Experimental results carried out on a simulated noisy image and on true data from a modern generation airborne imaging spectrometer highlight the accuracy of the proposed method and its robustness to image textures that may lead to a gross overestimation of the noise, especially for high SNR.
Image and Signal Processing for Remote Sensing IV, 1998
ABSTRACT This paper reports about a quantitative evaluation of pyramid- based schemes performing ... more ABSTRACT This paper reports about a quantitative evaluation of pyramid- based schemes performing a feature-based fusion of data from multispectral and panchromatic imaging sensors having different ground resolutions. A critical point is performances evaluation of image data fusion. A set of quantitative parameters has been recently proposed. Both visual quality, regarded as contrast, presence of fine details, and absence of impairments and artifacts (e.g., blur, ringing), and spectral fidelity (i.e., preservation of spectral signatures) are concerned and embodied in the measurements. The aim of the present work is to provide a comprehensive performance comparison on SPOT data among three feature-based schemes for image fusion, as well as on a specific case study on which multisensor observations were available. Out of the three methods compared, respectively based on high-pass filtering (HPF), wavelet transform (WT), and generalized Laplacian pyramid (GLP), the latter two are far more efficient than the former, thus establishing the advantages for data fusion of a formally multiresolution analysis.
Proceedings of SPIE - The International Society for Optical Engineering
In this work, a multi-resolution procedure based on a generalized Laplacian pyramid (GLP), with p... more In this work, a multi-resolution procedure based on a generalized Laplacian pyramid (GLP), with p:q (i.e. rational) scale factor, is proposed to merge image data of any resolution and represent them at any scale. The GLP- based data fusion is shown to be slightly superior to those of a similar scheme based on the discrete wavelet transform (WT), according to a set of parameters established in the literature. Not only fused images look sharper than their original versions, but also textured regions are enhanced without losing their spectral signatures. The pyramid- generating filters can be easily designed for data of any resolutions, differently from the WT, whose filter-bank design is non-trivial when the ratio between the scales of the images to be merged is not a power of two. Eventually, remotely sensed images from LandSat TM and from Panchromatic SPOT are fused together. The resulting bands capture multi- spectral features with enhanced contrast and texture, and an increased sp...
Proceedings of SPIE - The International Society for Optical Engineering
Speckle reduction in synthetic aperture radar (SAR) images is a key point to facilitate applicati... more Speckle reduction in synthetic aperture radar (SAR) images is a key point to facilitate applicative tasks. A filter aimed at speckle reduction should energetically smooth homogeneous regions, while preserving point targets, edges, and linear features. A tradeoff, however, should be arranged on textured areas. Filtering capabilities depend on local image characteristics, and generally no filter outperforms the others in every situation. In this work, a set of adaptive filters is considered with attention to those oriented towards a multiresolution approach. Images are individually processed by each filter, and the output at each pixel position is obtained by choosing one out of the channels. The selection is based on thresholding local features accounting for both space-varying statistics and geometry. Results on true SAR images show that also an empirical choice of thresholds is noncritical: the novel scheme outperforms each filter individually, at least according to visual criteria.
Proceedings of SPIE - The International Society for Optical Engineering
Several attempts have been made to merge Landsat TM multispectral data with high spatial resoluti... more Several attempts have been made to merge Landsat TM multispectral data with high spatial resolution panchromatic SPOT images. In this work a multiresolution approach based on a generalized Laplacian pyramid with p:q (i.e., rational) scale factor is proposed to merge image data of any resolution and represent them at any scale. The resulting bands capture multispectral characteristics with an enhanced spatial resolution, thereby expediting visual analysis and contextual interpretation of the environment according to archaeological issues. Objective and subjective evaluations show the effectiveness of the proposed method.
Uploads
Papers by Bruno Aiazzi