Progressive image coding based on an adaptive block compressed sensing

Clustering compressed sensing based on image block similarities

Compressed sensing (CS) algorithm enables sampling rates significantly under classical Nyquist rate without sacrificing reconstructed image quality. It is known that, a great number of images have many similar areas which are composed by the same number of grayscale or color. A new CS scheme, namely clustering compressed sensing (CCS), was proposed for image compression, and it introduces clust...

Bit-plane Image Coding Scheme Based On Compressed Sensing

Based on compressed sensing, a new bit-plane image coding scheme was presented. Due to different important for different image bit-plane, the new method is robust to bit error, and has the advantages of simple structure and easy software and hardware implementation. Because the values of the image bit-plane are 1 or zero, one order difference matrix was chosen as sparse transform matrix, and th...

Adaptive compressed image sensing based on wavelet-trees

We present Adaptive Direct Sampling (ADS), an improved algorithm for simultaneous image acquisition and compression which does not require the data to be sampled at its highest resolution. In some cases, our approach simplifies and improves upon the existing methodology of Compressed Sensing (CS), by replacing the ‘universal’ acquisition of pseudo-random measurements with a direct and fast meth...

Block Transforms in Progressive Image Coding

Adaptive Wavelet Image Block Coding

In this paper a new approach for adaptive wavelet image coding is introduced. Based on an adaptive quadtree image-block partition (similar to fractal coding) the diierent image blocks may be compressed independently in an adaptive manner. In order to adapt to local image statistics and features we present several possibilities how to optimize the transform part of a wavelet image block-coder. A...