Abstract: A method of losslessly compressing and encoding signals representing image information is claimed. A lossy compressed data file and a residual compressed data file are generated. When the lossy compressed data file and the residual compressed data file are combined, a lossless data file that is substantially identical to the original data file is created.

Abstract: A method and system for increasing the detection, location, identification or classification of objects hidden on the surface or buried below the surface of the ground is disclosed. The method acquires image data in separate IR and/or visible spectral regions simultaneously and converts the data into intensity value arrays for each spectral region. These intensity value arrays are transformed into two-dimensional discrete wavelet transform arrays for each spectral region. The background clutter from the two-dimensional discrete wavelet transform arrays is removed; forming clutter reduced two-dimensional discrete wavelet transform arrays. The inverse two-dimensional discrete wavelet transform is performed on the clutter reduced two-dimensional discrete wavelet transform arrays to form clutter removed intensity value arrays. These arrays are subtracted in a pair-wise mariner to obtain chemical-specific spectral signatures.

Abstract: A method of losslessly compressing and encoding signals representing image information is claimed. A lossy compressed data file and a residual compressed data file are generated. When the lossy compressed data file and the residual compressed data file are combined, a lossless data file that is substantially identical to the original data file is created.

Abstract: A method of losslessly compressing and encoding signals representing image information is claimed. A lossy compressed data file and a residual compressed data file are generated. When the lossy compressed data file and the residual compressed data file are combined, a lossless data file that is substantially identical to the original data file is created.

Abstract: A method of losslessly compressing and encoding signals representing image information is claimed. A lossy compressed data file and a residual compressed data file are generated. When the lossy compressed data file and the residual compressed data file are combined, a lossless data file that is substantially identical to the original data file is created.

Abstract: A method of losslessly compressing and encoding signals representing image information is claimed. A lossy compressed data file and a residual compressed data file are generated. When the lossy compressed data file and the residual compressed data file are combined, a lossless data file that is substantially identical to the original data file is created.

Abstract: The present invention is a processing method to increase the detection of objects below the surface of the water comprising the steps of: acquiring image data in separate spectral regions simultaneously and converting the image data into intensity value arrays for each spectral region, transforming the intensity value arrays into two-dimensional discrete wavelet transform arrays for each spectral region, and subtracting in a pair wise manner the two-dimensional discrete wavelet transform arrays thereby obtaining images showing an object below the surface of the water.

Abstract: A method and system for increasing the detection, location, identification or classification of objects hidden on the surface or buried below the surface of the ground is disclosed. The method acquires image data in separate IR and/or visible spectral regions simultaneously and converts the data into intensity value arrays for each spectral region. These intensity value arrays are transformed into two-dimensional discrete wavelet transform arrays for each spectral region. The background clutter from the two-dimensional discrete wavelet transform arrays is removed; forming clutter reduced two-dimensional discrete wavelet transform arrays. The inverse two-dimensional discrete wavelet transform is performed on the clutter reduced two-dimensional discrete wavelet transform arrays to form clutter removed intensity value arrays. These arrays are subtracted in a pair-wise mariner to obtain chemical-specific spectral signatures.

Abstract: A method of losslessly compressing and encoding signals representing image information is claimed. A lossy compressed data file and a residual compressed data file are generated. When the lossy compressed data file and the residual compressed data file are combined, a lossless data file that is substantially identical to the original data file is created.

Abstract: The present invention is a processing method to increase the detection of objects below the surface of the water comprising the steps of: acquiring image data in separate spectral regions simultaneously and converting the image data into intensity value arrays for each spectral region, transforming the intensity value arrays into two-dimensional discrete wavelet transform arrays for each spectral region, and subtracting in a pair wise manner the two-dimensional discrete wavelet transform arrays thereby obtaining images showing an object below the surface of the water.

Abstract: A system and method for quality-based image compression utilizing adaptively sized blocks and sub-blocks of discrete cosine transform coefficient data and a quality based quantization scale factor is claimed. A block size assignment element in an encoder element selects the block or sub-block of an input block of pixel data to be processed. Blocks with variances larger than a threshold are subdivided, while blocks with variances smaller than a threshold are not subdivided. A transform element transforms the pixel values of the selected blocks into the frequency domain. The frequency domain values are quantized either on a block by block basis or a frame by frame basis utilizing a scale factor that correlates with the quality of the image. The data is then serialized and coded in preparation for transmission.

Abstract: A system and method for quality-based image compression utilizing adaptively sized blocks and sub-blocks of discrete cosine transform coefficient data and a quality based quantization scale factor is claimed. A block size assignment element in an encoder element selects the block or sub-block of an input block of pixel data to be processed. Blocks with variances larger than a threshold are subdivided, while blocks with variances smaller than a threshold are not subdivided. A transform element transforms the pixel values of the selected blocks into the frequency domain. The frequency domain values are quantized either on a block by block basis or a frame by frame basis utilizing a scale factor that correlates with the quality of the image. The data is then serialized and coded in preparation for transmission.

Abstract: A system and method for quality-based compression utilizing adaptively sized blocks and sub-blocks of discrete cosine transform coefficient data and a quality based quantization scale factor is claimed. A block size assignment element in an encoder element selects the block or sub-block of an input block of pixel data to be processed. Blocks with variances larger than a threshold are subdivided, while blocks with variances smaller than threshold are not subdivided. A transform element transforms the pixel values of the selected blocks into the frequency domain. The frequency domain values are quantized either on a block by block basis or a frame by frame basis utilizing a scale factor that correlates with the quality of the image. The data is then serialized and coded in preparation for transmission.