Abstract: Provided is a process and system for detection of sparse or otherwise weak targets in a hyperspectral image. A hyperspectral image is received having a multitude of pixels, with each pixel having a respective spectrum. In some embodiments, multiple mean spectra are selectively determined for respective sub-regions of the hyperspectral image. The subset mean spectra can be selectively removed from respective pixels, thereby improving image fidelity due to sensor artifacts. Additionally, target detection of such an adjusted image can be determined by one or more of matched filter techniques or by partial un-mixing. In at least some embodiments target detection is enhanced by combining a measure of target match with a residual spectrum determined as a measure of un-match. Target detection can be further improved by application of rules, for example, related to target detection threshold.

Abstract: The invention relates to a method of evaluating the confidence of matching signatures of a hyperspectral image of at least one tracked object, defined by pixels on an image sensor, to a hyperspectral image template in real time while tracking the at least one tracked object.

Abstract: An image reading apparatus according to one aspect of the present disclosure includes a document sheet table, a first carriage, a photoelectric converting portion, and a position detecting portion. First carriage has lighting portion. Position detecting portion detects initial position in reciprocating of first carriage. Lighting portion includes: light guide member on which the light from light source is incident, and which guides incident light in primary scanning direction and applies the light to document sheet table; and heat dissipating member that dissipates heat generated in light source. Position detecting portion includes: light emitter that emits light; light receiver that receives light emitted from light emitter; and detection member that moves in secondary scanning direction along with reciprocating of first carriage, in order to detect initial position of first carriage.

Abstract: The present invention evaluates the quality of an image shot by a terminal device in a state closer to that seen with the eye. A computer evaluates the quality of an image obtained by shooting a photographic subject including a periodic pattern that fluctuates periodically in one direction. A Fourier transform unit accomplishes a two-dimensional Fourier transform on the image to obtain two-dimensional spatial frequency spectrum components. An analysis unit analyzes the resolution of the image on the basis of spectrum components of spatial frequencies included in the periodic pattern, among the two-dimensional spatial frequency spectrum components obtained by the Fourier transform unit, and analyzes the deterioration of the image on the basis of spectrum components other than these.

Abstract: A search for a target in a multispectral image is made more efficient and more user-friendly by combining a contrast optimization which is performed locally, with a presentation of a detection image which extends over the entire field of observation (10). The contrast is optimized inside a window (2) of reduced size relative to an image matrix (1) corresponding to the entire field of observation. This window may be moved in conjunction with the direction of observation (D), or it may be selected at will in the image matrix. The detection image may be renewed for each window used, or it may be shared by several windows.

Abstract: A system for determining an aspect ratio of image content based on an analysis of the content. In an embodiment, an analyzer is configured to receive a data input corresponding to an image in a stream of images that constitute a video sequence of images. The analyzer is further configured to determine a mathematical representation of the image content based on a power spectrum analysis of vertical components of the image in comparison to a power spectrum analysis of horizontal components of the image. Based on this comparison of the vertical frequency components to the horizontal frequency components, a determination about the original aspect ratio of the image may be determined. This determination may be used by a video processor to correctly apply aspect ratio conversion for final image output.

Abstract: Exemplary embodiments disclose an image processing method which includes obtaining a binary value by quantizing a value obtained by summing at least one pixel value of an input image and a quantization error value of a neighboring pixel; determining a pixel in which a detail intensity is to be inserted according to the binary value of each pixel; determining the detail intensity to be inserted in the determined pixel; and inserting the determined detail intensity in the determined pixel, wherein the quantization error value of the neighboring pixel is a difference value between an original pixel value of the neighboring pixel and a pixel value quantized with respect to a predetermined constant value.

Abstract: A moving image capture apparatus generates a data file to record, on a recording medium, an image signal output from an imaging unit, extracts character information from the image signal to be recorded on the recording medium, sets a parameter value used for selection as a file name according to a characteristic of appearance of the character information, calculates an evaluation value from the set parameter value, and sets character information based on the calculated evaluation value as a file name of the image signal. Furthermore, the moving image capture apparatus generates a thumbnail of the file based on an image signal from which character information for which the calculated evaluation value is relatively large has been extracted.

Abstract: A video image feature generation system includes a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute, extracting a frame feature value featuring a frame, which is a unit of an input video image, based on a pixel value of the frame; and generating a phase of each frequency as a video image feature based on at least two frequencies, the frame feature value obtained in the extracting, and generation information for generating phases of the frequencies according to the frequencies and the frame feature value.

Abstract: The present invention provides an inspection device including an imaging unit 16 for imaging an object to be inspected, a characteristics measurement unit 15 for measuring characteristics of the object to be inspected, an inspection information acquisition unit 11 for acquiring inspection information related to the object to be inspected, a condition determination unit 12 for determining measurement information related to a measurement condition of the object to be inspected corresponding to the inspection information, an imaging control unit 14 for controlling imaging by the imaging unit, and a measurement control unit 13 for controlling measurement by the characteristics measurement unit based on the measurement information.

Abstract: A video image capture component includes a light source operable in a first spectrum, a first image detector operable in the first spectrum, a second light source operable in a second spectrum, and a second image detector operable in the second spectrum. A filtering component generates a combination image by filtering a first image obtained by the first image detector with a high-contrast filter, resulting in a high-contrast image, and masking a second image obtained by the second image detector using the high-contrast image. A compositing component creates a composite image from the combination image and a selected image. A display component displays the composite image. Alternative systems and methods for creating a combination image include techniques involving thermal imaging, laser detection, and narrow band frequency detection.

Abstract: The invention relates to localizing the position of a person speaking by using pictures of a pattern (21) on an object (20) worn by the person. The object (20) carries a complex pattern (21) that is optimized for determining the orientation of the object (20), the distance from the object to a microphone device (14) and/or to a camera (11). Moreover, the pattern (21) may be arranged for identifying the person carrying the object (20). The determination of the position of the person carrying the object (20) may be used to enhance speech recognition (SR) and/or to provide hands-free voice control of devices (DC), e.g. in hospitals or in industrial settings.

Abstract: In accordance with various aspects of the disclosure, a detecting engine for detecting targets/materials in hyperspectral scenes is disclosed. The detecting engine combines data partitioning and dimensionality reduction to reduce the number of computations needed to identify in which pixels in a hyperspectral scene a given material is present. Computation reduction (in some instances, by two fold) greatly impacts the speed of and power consumed by the detecting engine making the engine suitable for hyperspectral imaging of large scenes, processing using many filters per pixel, or missions requiring testing large numbers of reference spectra to see which are present in a scene.

Abstract: A method of spectral-spatial-temporal image detection is disclosed. In one embodiment, a spectrally differenced image is obtained by computing a difference of at least two intensity values in at least two spectral bands of an image. Further, a spatially filtered spectral image is obtained by applying a spatial median filter to the obtained spectrally differenced image. Furthermore, a temporal image is obtained by determining a temporal pixel value difference using a computed predictive frame difference. In addition, a spectral-spatial-temporal filtered image for detection is obtained by using the obtained spatially filtered spectral image and the temporal image.

Abstract: Provided is a method of hyperspectral image dimension reduction. The method includes receiving a hyperspectral image having a plurality of pixels. A set of basis vectors is established at least in part with respect to the spectral vectors of the initial hyperspectral image. For each pixel of the hyperspectral image, the spectral vector is read and decomposed, i.e. unmixed, with the basis vector set to provide at least a reduced dimension vector for each pixel. Collectively the reduced dimension vectors for each pixel represent the dimensionally reduced image. A system operable to perform the method is also provided.

Abstract: What is disclosed is a system and method for estimating color for pixels in an infrared image. In one embodiment, an infrared image is received which has been captured using a N-band infrared imaging system comprising a multi-spectral camera or a hyperspectral camera. The IR image is composed of an array of pixels with N intensity values having been collected for each pixel in the image. Then, for each pixel of interest, a search metric is used to search a database of vector samples to identify a visible-IR set which is closest to the intensity values of the IR band vector collected for the pixel. A visible vector representation is then estimated for the pixel based upon the visible portion corresponding to the closest visible-IR set. Thereafter, color coordinates for this pixel are computed from the visible vector. The method repeats for all pixels of interest in the IR image.

Abstract: The mobile unit position detecting apparatus generates target data by extracting a target from an image shot by the image capturing device, extracts target setting data that best matches the target data, is prerecorded in a recording unit and is shot for each target, obtains a target ID corresponding to the extracted target setting data from the recording unit, detects position data associated with the obtained target ID, tracks the target in the image shot by the image capturing device, and calculates an aspect ratio of the target being tracked in the image. If the aspect ratio is equal to or lower than a threshold value, the mobile unit position detecting apparatus outputs the detected position data.

Abstract: The invention concerns a method of performing, by an image processing device, object detection in an image comprising: performing one or more tests of a test sequence for detection of a first object on pixels values of a plurality of at least partially overlapping sub-regions (310, 312, 314) of a first search window (108); generating a cumulative score based on results of said one or more tests on said plurality of sub-regions; comparing said cumulative score with a threshold value; and based on said comparison, selectively performing one or more of said tests of said test sequence on at least one further sub-region of said first search window, said at least one further sub-region at least partially overlapping each of said plurality of sub-regions.

Abstract: In accordance with various aspects of the disclosure, a method, system, and computer readable media having instructions for processing images is disclosed. For example, the method includes determining a suspicious pixel suspected of causing an artifact in a measurement as a function of a statistical analysis of a collection of samples representing residual error values associated with a subject focal plane pixel measuring one waveband at different times. Based on the determination of the suspicious pixel, a pattern of residual error values is identified that is indicative of the artifact caused by the suspicious pixel. A correcting time-dependent offset determined that is substantially reciprocal to the identified pattern of residual error values. The correcting time-dependent offset is applied to the measurement to correct for artifact in the measurement.

Abstract: A system and method are provided to operate upon image data electronically captured with complex spectral content in a plurality of image data pixels within a spatial image plane. A plurality of reference components are provided. A discovery processor is coupled to the general dictionary, and is programmably configured to execute a simultaneous sparse approximation process upon image data pixels of at least a portion of the captured image. The discovery processor discovers therefor a set of core spectral signatures defined in terms of selected reference components from the general dictionary. A match processor programmably configured to execute a selective matching process is also provided for transforming individual image data pixels into linear combinations of selected core spectral signatures. The constituent features of the captured image portion corresponding to the selectively matched core spectral signatures are discriminated according to the linear combination thereof.

Abstract: An apparatus is described. The apparatus includes a digital camera that is capable of shooting at least two images at different effective lens focal lengths. The camera is also capable of high pass filtering (HP) said at least two images, estimating respective spectral densities (SD) of said at least two filtered images and then low pass filtering (LP) the respective estimates of said at least two filtered images prior to combining said at least two images into a single image to produce one or more optical effects.

Abstract: A method for reducing dimensionality of hyperspectral images includes receiving a hyperspectral image having a plurality of pixels. The method may further include establishing an orthonormal basis vector set comprising a plurality of mutually orthogonal normalized members. Each of the mutually orthogonal normalized members may be associated with one of the plurality of pixels of the hyperspectral image. The method may further include decomposing the hyperspectral image into a reduced dimensionality image, utilizing calculations performed while establishing said orthonormal basis vector set. A system configured to perform the method may also be provided.

Abstract: The present invention provides an inspection device including an imaging unit 16 for imaging an object to be inspected, a characteristics measurement unit 15 for measuring characteristics of the object to be inspected, an inspection information acquisition unit 11 for acquiring inspection information related to the object to be inspected, a condition determination unit 12 for determining measurement information related to a measurement condition of the object to be inspected corresponding to the inspection information, an imaging control unit 14 for controlling imaging by the imaging unit, and a measurement control unit 13 for controlling measurement by the characteristics measurement unit based on the measurement information.

Abstract: A method and an apparatus for processing an image generates, using a linear embedding operator, a second set of feature points from a first set of feature points of the image, so that a pair-wise nearest neighbor (NN) topological relationship among the first set of feature points is preserved in the second set of feature points. The linear embedding operator is determined by an affinity model comprising a first affinity parameter, a second affinity parameter, and an affinity matrix, wherein a sparsity of the affinity matrix is controlled by the first affinity parameter and the second affinity parameter.

Abstract: Relative changes in organic matter in soil in an agricultural field are mapped by a computer-implemented system and method that uses a number of individual bands from one or more remotely sensed images of the agricultural field. Each of the bands is associated with a light spectrum wavelength range, and each of the bands is weighted based on its contribution to predicting relative changes in organic matter. Elevation data may also be used in the weighted calculation. The map is separated into zones based on the relative predicted organic matter falling within a predefined range. Each zone may be associated with a different average organic matter content, and nutrient supplements are recommended for each zone based on the average organic matter associated with each of the mapped zones.

Abstract: The present invention evaluates the quality of an image shot by a terminal device in a state closer to that seen with the eye. A computer evaluates the quality of an image obtained by shooting a photographic subject including a periodic pattern that fluctuates periodically in one direction. A Fourier transform unit accomplishes a two-dimensional Fourier transform on the image to obtain two-dimensional spatial frequency spectrum components. An analysis unit analyzes the resolution of the image on the basis of spectrum components of spatial frequencies included in the periodic pattern, among the two-dimensional spatial frequency spectrum components obtained by the Fourier transform unit, and analyzes the deterioration of the image on the basis of spectrum components other than these.

Abstract: Methods, storage mediums and systems (MS&S) are provided which successively image an imaging region of an assay analysis system (AAS) as particles are loaded into the imaging region, generate a frequency spectrum of each image via a discrete Fourier transform, integrate a same coordinate portion of each frequency spectrum and terminate the loading of particles upon computing an integral which meets preset criterion. In addition, MS&S are provided which send a signal indicative of whether enough particles are in an imaging region for further processes by an AAS based on the magnitude of integral calculated from an image's frequency spectrum. MM&S are also provided such that the steps of generating a frequency spectrum of each image and integrating a portion of each frequency spectrum are replaced by generating a convolved spatial image with a filter kernel and integrating a same coordinate portion of each convolved spatial image.

Abstract: The present invention evaluates the quality of an image shot by a terminal device in a state closer to that seen with the eye. A computer evaluates the quality of an image obtained by shooting a photographic subject including a periodic pattern that fluctuates periodically in one direction. A Fourier transform unit accomplishes a two-dimensional Fourier transform on the image to obtain two-dimensional spatial frequency spectrum components. An analysis unit analyzes the resolution of the image on the basis of spectrum components of spatial frequencies included in the periodic pattern, among the two-dimensional spatial frequency spectrum components obtained by the Fourier transform unit, and analyzes the deterioration of the image on the basis of spectrum components other than these.

Abstract: A method and system for producing accented image data for an accented image is disclosed. The method includes decomposing each of a first and a second image into a gradient representation which comprises spectral and edge components. The first image comprises more spectral dimensions than the second image. The edge component from the first image is combined with the spectral component from the second image to form a combined gradient representation. Accented image data for the accented image is then generated from data including the combined gradient representation.

Abstract: The disclosure concerns processing of electronic images, such as hyperspectral or multispectral images. In particular, but is not limited to methods, software and computer systems for determining underlying spectra of an image of a scene. The image data comprises for each pixel location a sampled image spectrum that is a mixture of plural reflectance spectra. Processor 310 determines or accesses plural hyperplanes that each have plural linearly independent basis vectors. Each hyperplane represents an estimate of one of the plural reflectance spectra. The processor 310 then determines for each pixel location, a contribution of the plural basis vectors of each hyperplane to the image spectrum of that pixel location. The processor 310 determines or accesses plural hyperplanes and not plural endmembers directly. Hyperplanes are two-dimensional while endmembers are only one-dimensional. As a result, hyperplanes carry more information, such as the illumination spectrum and are therefore of greater use.

Abstract: A method and system for estimating atmospheric radiance and transmittance. An atmospheric estimation system is divided into a first phase and a second phase. The first phase inputs an observed multispectral image and an initial estimate of the atmospheric radiance and transmittance for each spectral band and calculates the atmospheric radiance and transmittance for each spectral band, which can be used to generate a “corrected” multispectral image that is an estimate of the surface multispectral image. The second phase inputs the observed multispectral image and the surface multispectral image that was generated by the first phase and removes noise from the surface multispectral image by smoothing out change in average deviations of temperatures.

Abstract: A method of clustering and reducing hyperspectral image data having a plurality of spatial pixels, and a plurality of spectral dimensions associated with each spatial pixel, includes computing an initial basis vector associated with the hyperspectral image data, unmixing the initial basis vector with the hyperspectral image data to generate an initial set of coefficients and an associated set of residual vectors, generating a set of clusters based on the initial set of coefficients, and iteratively computing one or more additional basis vectors and updating the set of clusters. The iterative computing includes calculating a subsequent basis vector based on a residual vector associated with a prior unmixing, unmixing the subsequent basis vector with a prior set of residual vectors to generate additional coefficients associated with each pixel, and iteratively computing cluster centers and content including an additional dimension associated with the subsequent basis vector.

Abstract: The invention relates to a method of selecting an algorithm for use in processing hyperspectral data from a set of algorithms, each having qualities for processing certain characteristics of hyperspectral data.

Abstract: The invention relates to a method of evaluating the confidence of matching signatures of a hyperspectral image of at least one tracked object, defined by pixels on an image sensor, to a hyperspectral image template in real time while tracking the at least one tracked object.

Abstract: A method of deriving a representation of an image by processing signals corresponding to the image, the method comprises deriving a function of the image, where a function of a translated, scaled or rotated version of the image is a translated or scaled version of the derived function of the image, and using a plurality of frequency components of a frequency representation of the function to derive a representation of the image.

Abstract: Computer implemented methods for compressing 3D hyperspectral image data having a plurality of spatial pixels associated with a hyperspectral image, and a number of spectral dimensions associated with each spatial pixel, include receiving, using a processor, the 3D hyperspectral image data, a set of basis vectors associated therewith, and either a maximum error amount or a maximum data size. The methods also include partitioning the 3D hyperspectral image data into a plurality of 2D images, each associated with one of the number of spectral dimensions, and an associated one of the set of basis vectors. The methods additionally include ranking the set of basis vectors if not already ranked. The methods may further include iteratively applying lossy compression to the 2D images, in an order determined by the ranking. Other embodiments and features are also disclosed.

Abstract: A system and method of correcting a depth map for 3D image is disclosed. A spatial spectral transform unit extracts pixels of object boundaries according to an input image, wherein the spatial spectral transform unit adopts Hilbert-Huang transform (HHT). A correction unit corrects an input depth map corresponding to the input image according to the pixels of object boundaries, thereby resulting in an output depth map.

Abstract: Apparatus, systems, and methods integrating spectral information with spatial feature extraction of image data, providing simultaneous spatial and spectral feature selection of the image data, can be used in a variety of applications. In various embodiments, an edge signature for the edge between two materials can be defined using ratios of identified spectral bands, where the edge signature can be combined with a spatial mask to obtain a joint spatio-spectral mask. Additional apparatus, systems, and methods are disclosed.

Abstract: Methods, systems and computer program products for managing frequency domain optical coherence tomography (FDOCT) image resolution. A spectrum used to acquire an image of a subject is calibrated and default dispersion correction parameters are set. Default dispersion management parameters associated with a region of the image of the subject are also set. The image of the subject is acquires after setting the default dispersion correction parameters and the default dispersion management parameters. A quality of the acquired image is compared to a quality metric for the acquired image. The dispersion correction parameters are adjusted if the quality of the acquired image does not meet or exceed the quality metric for the acquired image. The acquired image is reprocesses based on the adjusted dispersion correction parameters. The steps of comparing, adjusting and reprocessing are repeated until the acquired image meets or exceeds the quality metric for the acquired image.

Abstract: The disclosure concerns hyperspectral and multispectral image. The disclosure concerns the computation of a descriptor for such an image. The descriptor can be used in a range of image post-processing applications, such as classification, recognition, tracking and localization. Aspects of the invention include a computer implemented method and a computer system. To computer the descriptor for a set of wavelength indexed bands, a band representation of the radiance measurements for that band based on a probability distribution function is computed 300. Then a wavelength-dependent cross-correlation between the band representations is computed 302. Finally, a descriptor based on the computed cross-correlation between the band representations is computed 304. It is an advantage that the descriptor captures a discriminative and descriptive representation of scene captured in the hyperspectral or multispectral image.

Abstract: Systems and methods for backlit scene detection are described. The method includes performing a pre-test on an electronic image to determine that the electronic image does not include a disqualifying characteristic. Next, the method includes performing a type test on the electronic image to determine an image type of the electronic image from a first set of predetermined backlit image types. Next the method includes performing a post test on the electronic image to determine that the image darkness density does not exceed a predetermined density. Finally, the method includes performing a second post test on the electronic image to determine that the electronic image is one of a second set of predetermined backlit image types or that the edge percentage of the electronic image exceeds a predetermined percentage.

Abstract: Techniques are provided for mesoscopic geometry modulation. A first set of mesoscopic details associated with an object is determined by applying a filter to an image of an object. Mesoscopic details included in the first set of mesoscopic details are detectable in the image of the object and are not detectable when generating a coarse geometry reconstruction of the object. A three-dimensional model for the object is generated by modulating the coarse geometry with the first set of mesoscopic details.

Abstract: A method and apparatus for image automatic brightness detection. The method includes determining region of interest (ROI) candidates in an image, extracting features from each of the ROI candidates, selecting the optimum ROI based on weighted score of each of the ROI candidate, and calculating brightness value of the selected optimum ROI candidate as brightness feedback. The method and apparatus for image automatic brightness detection according to embodiments of the present invention, can automatically detect the point of interest for clinicians, and then provide a more accurate feedback to the imaging system, in order to provide a more efficient dose management in the imaging system and thus to achieve constant image quality without wasting any dose, thereby further optimizing the dose/IQ performance and the high efficient utilization of the system.

Abstract: Techniques for tracking one or more objects at each position in an interval in a video input with the use of a Kalman filter, including obtaining a first location estimate of an object with an object detector, obtaining a second location estimate and a movement estimate of the object with an object tracker, determining a final estimate of a position and/or a velocity of the object with the Kalman filter.

Abstract: Statistical analysis techniques based on auto- and cross-correlations/cumulants, of image stacks of fluctuating objects are used to improve resolution beyond the classical diffraction limit and to reduce the background. The time trajectory of every pixel in the image frame is correlated with itself and/or with the time trajectory of an adjacent pixel. The amplitude of these auto- or cross-correlations/cumulants of each pixel, at a given time lag or averaged or integrated over an interval of time lags, is used as the intensity value of that pixel in the generated superresolved optical fluctuation image.

Abstract: An imaging or data processing method using statistical analysis to determine features of interest in an image or data set. Particular implementations of the imaging or data processing methods relate to refining the results of an image processing method using iterative examination of posterior probabilities or external feedback.

Abstract: An image having m light sources, with m preferably equaling 2 or 3, is segmented into different regions, each of which is lit by only one of the m light sources, by obtaining paired imaged with different filtering, for example a filtered and an unfiltered image, applying to the image pairs sets of m pre-computed mappings at the pixel or region level, and selecting the most appropriate. The rendering of the information in the image maybe adjusted accordingly.

Abstract: A system for processing hyperspectral image data includes one or more storage mediums comprising reduced dimensionality data associated with hyperspectral image data, a set of basis vectors associated with generating the reduced dimensionality data from the hyperspectral image data, and anomaly data associated with the hyperspectral image data. The system also includes one or more processors configured to establish an initial set of clusters for the reduced dimensionality data, the initial set of clusters having cluster centers being based on the set of basis vectors. The one or more processors are also configured to iteratively assign pixels from the reduced dimensionality data to one of the set of clusters and modify the cluster center based on the assigned pixels. The one or more processors are further configured to output clustered pixel assignments and modified cluster centers associated with the hyperspectral image data. Associated methods of processing are also disclosed.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, assembling a feature vector for the image file, the feature vector containing information regarding a likelihood that a selected pair of regions of the image file are of a same intrinsic characteristic, providing a classifier derived from a computer learning technique, computing a classification score for the selected pair of regions of the image file, as a function of the feature vector and the classifier and classifying the regions as being of the same intrinsic characteristic, as a function of the classification score.

Abstract: A method of image processing. A band-averaged spectral radiance is measured using at least one optical filter upon scanning a plurality of original radiances. The measured band-averaged spectral radiance includes a measured in-band-averaged spectral radiance and a measured band-gap-averaged spectral radiance. A multispectral radiance vector is generated from the measured band-averaged spectral radiance. The multispectral radiance vector and an out-of-band correction transform matrix corresponding to the at least one optical filter are matrix-multiplied to generate a band-averaged spectral radiances image vector representing a plurality of recovered band-averaged spectral radiances. The plurality of recovered band-averaged spectral radiances is analyzed for a presence of a target.