Context-based entropy coding of block transform coefficients for image compression

Context-based entropy coding of block transform coefficients for image compression

It has been well established that state-of-the-art wavelet image coders outperform block transform image coders in the rate-distortion (R-D) sense by a wide margin. Wavelet-based JPEG2000 is emerging as the new high-performance international standard for still image compression. An often asked question is: how much of the coding improvement is due to the transform and how much is due to the enc...

Eecient Context-based Entropy Coding for Lossy Wavelet Image Compression

In this paper we present an adaptive image coding algorithm based on novel backwardadaptive quantization/classi cation techniques. We use a simple uniform scalar quantizer to quantize the image subbands. Our algorithm puts each coe cient into one of several classes depending on the values of neighboring previously quantized coe cients. These previously quantized coe cients form contexts which a...

Efficient Context-Based Entropy Coding Lossy Wavelet Image Compression

Context modeling and entropy coding of wavelet coefficients for image compression

In this paper we study the problem of context modeling and entropy coding of the symbol streams generated by the well-known EZW image coder (embedded image coding using zerotrees of wavelet coe cients). We present some simple context modeling techniques that can squeeze out more statistical redundancy in the wavelet coe cients of EZW-type image coders and hence lead to improved coding e ciency.

Adaptive block-size transform coding for image compression

In this paper we report the results of an adaptive blocksize transform coding scheme that is based on the sequential JPEG algorithm. This minimum informationoverhead method implies a transform coding technique with two di erent block sizes: N N and 2N 2N pixels. The input image is divided into blocks of 2N 2N pixels and each of these blocks is classi ed according to its image activity. Dependin...