Line-based, reduced memory, wavelet image compression

Abstract

This paper addresses the problem of low memory wavelet image compression. While wavelet or subband coding of images has been shown to be superior to more traditional transform coding techniques, little attention has been paid until recently to the important issue of whether boththe wavelet transforms and the subsequent coding can be implemented in low memory without signi cant loss in performance. We present a complete system to perform low memory wavelet image coding. Our approach is \line-based" in that the images are read line by line and only the minimum required number of lines is kept in memory. The main contributions of our work are two. First, we i n troduce a line-based approach for the implementation of the wavelet transform, which yields the same results as a \normal" implementation, but where, unlike prior work, we address memory issues arising from the need to synchronize encoder and decoder. Second, we propose a novel context-based encoder which requires no global information and stores only a local set of wavelet coe cients. This low memory coder achieves performance comparable to state of the art coders at a fraction of their memory utilization.

A Survey of Image Compression Algorithms for Visual Sensor Networks

“…Our goal is not to survey all DWT implementations suggested in the literature, but rather we review algorithms applicable to VSN. The line-based version of the image wavelet transform proposed in [51,52] employs a buffer system where we store only a subset of the wavelets coefficients. That is, a considerable reduction in memory is observed, compared to the traditional transform approach.…”

“…The picture dimension can be 256 × 256 using fixed-point arithmetic and 128 × 128 using floating-point arithmetic. Compared to [51,52], the line-based method cannot run on a sensor with very small memory. The fractional wavelet filter method reduces the memory requirements compared to the linebased approach.…”

A VLSI architecture of JPEG2000 encoder

“…At the same time, the LL coefficients are written back to the processor in preparation for the next level of decomposition. Line based transform [7] is utilized to guarantee the tile is read line by line only once. The proposed architecture is shown in Fig.…”

Parallelization of Wavelet Filters Using Simd Extensions

“…The horizontal filtering is not that straight forward to parallelize. The same problem arises in 1-D transforms and applications with memory constraints [10]. The reason for this is that consecutive data that is read into a single packed word requires treatment that changes from word to word because of badly aligned filters and down-sampling.…”