Statistically Matched Wavelet Based Texture Synthesis in a Compressive Sensing Framework

Abstract

This paper proposes a statistically matched wavelet based textured image coding scheme for efficient representation of texture data in a compressive sensing (CS) frame work. Statistically matched wavelet based data representation causes most of the captured energy to be concentrated in the approximation subspace, while very little information remains in the detail subspace. We encode not the full-resolution statistically matched wavelet subband coefficients but only the approximation subband coefficients (LL) using standard image compression scheme like JPEG2000. The detail subband coefficients, that is, HL, LH, and HH, are jointly encoded in a compressive sensing framework. Compressive sensing technique has proved that it is possible to achieve a sampling rate lower than the Nyquist rate with acceptable reconstruction quality. The experimental results demonstrate that the proposed scheme can provide better PSNR and MOS with a similar compression ratio than the conventional DWT-based image compression schemes in a CS framework and other wavelet based texture synthesis schemes like HMT-3S.

New context of compression problem and approach to solution: a survey of the literature

“…Advanced signal processing tools like SMW and DEMD provide very efficient representation of the texture data and can be effectively used for texture video compression. Statistically Matched Wavelet based texture representation results in most of the captured energy to be concentrated in the approximation sub-space, while very little information is remains in the detail sub-space [179].…”

“…Motivated by these observations, we have proposed an application of Statistically Matched Wavelet for efficient representation of the texture data and an efficient texture synthesis in a compressive sensing framework [179]. In this work, We propose to encode not the full-resolution statistically matched wavelet sub-band coefficients (as normally done in a standard wavelet based image compression) but only the approximation sub-band coefficients (LL) using a standard image compression scheme like JPEG2000(which accounts for 1/4th of the total coefficients and can be represented using fewer bits).…”