<title>Finite-precision analysis of the JPEG-2000 compression standard</title>

Abstract

This study describes a detailed study of the effect of finite precision computation on wavelet-based image compression. Specifically, we examine how the quality of the final decoded image is affected by various choices that a hardware designed will have to make, such as choice of wavelet (integer or real), fixed-point attributes (number of integer and fractional bits), and compression. The algorithm studied here is that adopted by the JPEG 2000 committee, and it uses trellis-coded quantization on the wavelet coefficients, followed by bit-plane coding.

<title>Techniques for region coding in object-based image compression</title>

“…Compression and decompression errors in JPEG can result from (a) floating point errors or integer truncation errors in DCT, quantization, dequantization, and inverse DCT processes; as well as (b) errors in decompression during approximation of values input to the quantization and thresholding functions [31]. Propagation of these errors in JPEG have been analyzed elsewhere [32]. In practice, the author has observed that JPEG errors tend to be manifest as (a) obliteration of detail within a given encoding block, (b) small ringing artifacts in the decompression step, and (c) blocking effect.…”