Stereo image representation using compressive sensing

This paper presents a compressive sensing based stereo image representation technique using wavelet transform gain. The pair of input stereo images is first decomposed into its low-pass and high-pass views using a motion compensated lifting based wavelet transform. A 2D spatial wavelet transform is then further de-correlates the low-pass view into its sub-bands. Wavelet transform gains are employed to regulate threshold value for different sub-bands. The coefficients in high frequency sub-bands and high-pass view are then hard thresholded to generate their sparse sub-bands and view. The compressive sensing method is then used to generate measurements for different resulting sparse sub-bands and view. The baseband coefficients and measurements are finally losslessly coded. The application of compressive sensing in compressing natural images is in its early stages. Therefore, their performances are usually compared with each other than standard codecs. The performance of the proposed codec is superior to the state of the art and is superior to JPEG subjectively.