Coupled with the discrete wavelet transform, SPIHT (set partitioning in hierarchical trees) is a highly efficient image compression technique that allows for progressive transmission. One problem, however, is that its decoding can be extremely sensitive to bit errors in the code sequence. In this paper, we address the issue of transmitting SPIHT-encoded images via noisy channels, wherein errors are inevitable. The communication scenario assumed in this paper is that the transmitter cannot get any acknowledgement from the receiver. In our scheme, the original SPIHT code sequence is first segmented into packets. Each packet is classified as either a CP (critical packet) or an RP (refinement packet). For error control, cyclic redundancy check (CRC) is incorporated into each packet. By checking the CRC check sum, the receiver is able to tell whether a packet is correctly received or not. In this way, the noisy channel can be effectively modeled as an erasure channel. For unequal error protection (UEP), each of those packets are repeatedly transmitted for a few times, as determined by a process called diversity allocation (DA). Two DA algorithms are proposed. The first algorithm produces a nearly optimal decoded image (as measured in the expected signal-to-noise ratio). However, its computation cost is extremely high. The second algorithm works in a progressive fashion and is naturally compatible with progressive transmission. Its computation complexity is extremely low. Nonetheless, its decoded image is nearly as good. Experimental results show that the proposed scheme significantly improves the decoded images. They also show that making distinction between CP and RP results in wiser diversity allocation to packets and thus produces higher quality in the decoded images.

This paper presents a memory efficient version of set partitioning in hierarchical tree (SPIHT). The proposed coder called Memory Efficient SPIHT (MESH) uses a single re-usable list instead of three continuously growing linked lists as in conventional SPIHT. The list is re-initialized at the beginning of each bit-plane (coding pass) and is exhausted within the same bit-plane. Another feature of the proposed coder is that it uses a single pass for each bit-plane by merging the sorting and refinement passes of the conventional version of SPIHT. The performance of the proposed coder is measured in terms of coding efficiency, and the worst case dynamic memory requirements due to the list entries in each bit-plane. Performance comparison with SPIHT shows that the proposed coder reduces the dynamic memory requirement by about 50–70% compared to the SPIHT while retaining its coding efficiency.

We propose a moving picture coding by lapped transform and an edge adaptive deblocking filter to reduce the blocking distortion. We apply subband coding (SBC) with lapped transform (LT) and zero pruning set partitioning in hierarchical trees (zpSPIHT) to encode the difference picture. Effective coding using zpSPIHT was achieved by quantizing and pruning the quantized zeros. The blocking distortion caused by block motion compensated prediction is reduced by an edge adaptive deblocking filter. Since the original edges can be detected precisely at the reference picture, an edge adaptive deblocking filter on the predicted picture is very effective. Experimental results show that blocking distortion has been visually reduced at very low bit rate coding and better PSNRs of about 1.0 dB was achieved.

Set-partitioning in hierarchical trees (SPIHT) is one of the well-known image compression schemes. SPIHT offers an agreeable compression ratio and produces an embedded bit-stream for progressive transmission. However, the major disadvantage of SPIHT is its large memory requirement. In this paper, we propose a memory efficient SPIHT image coder and its parallel implantation. The memory requirement is reduced without sacrificing image quality. All bit-planes are concurrently encoded in order to speed up the entire coding flow. The result shows that the proposed algorithm is roughly 6 times faster than the original SPIHT. For a 512512 image, the memory requirement is reduced from 5.83 Mb to 491 Kb. The proposed algorithm is also realized on FPGA. With pipeline design, the circuit can run at 110 MHz, which can encode a 512512 image in 1.438 ms. Thus, the circuit achieves very high throughput, 182 MPixels/sec, and can be applied to high performance image compression applications.

Embedded zero-tree image coding in wavelet domain has drawn a lot of attention. Among noteworthy algorithms is the set partitioning in hierarchical trees (SPIHT). Typically, most of images' energy is concentrated in low frequency subbands. For an image with textures, however many middle-high frequency wavelet coefficients are likely to become significant in the early passes of SPIHT; thus the coding results are often insufficient. Middle and high frequency subbands of images may demand further decompositions using adaptive basis functions. As wavelet packet transform offers a great diversity of basis functions, we propose a quad-tree based adaptive wavelet packet transform to construct adaptive wavelet packet trees for zero-tree image coding. Experimental results show that coding performances can be significantly improved especially for fingerprints images.

Embedded zero-tree coding in wavelet domain has drawn a lot of attention for image compression applications. Among noteworthy zero-tree algorithms is the set partitioning in hierarchical trees (SPIHT) algorithm. For images with textures, high frequency wavelet coefficients are likely to become significant after a few scan passes of SPIHT, and therefore the coding results are often insufficient. It is desirable that the low frequency and high frequency components of an image are coded using different strategies. In this paper, we propose a hybrid algorithm using the SPIHT and EBC (embedded block coding) to code low frequency and high frequency wavelet coefficients, respectively; the intermediate coding results of low frequency coefficients are used to facilitate the coding operation of high frequency coefficients. Experimental results show that the coding performance can be significantly improved by the hybrid SPIHT-EBC algorithm.

In this paper, we propose an efficient method for rearranging the wavelet packet coefficients of an image to form hierarchical trees, by which the well known SPIHT algorithm can be applied. For images with textures, the high frequency wavelet coefficients are likely to become significant after several code passes of SPIHT, which degrades substantially the coding performance. As a result, the high frequency wavelet coefficients representing most of the high detail content of images need to be decomposed into wavelet packet coefficients for a further exploitation. The proposed rearrangement scheme has been applied to the highest frequency wavelet packet coefficients of images. Experimental results show that the performance of SPIHT can be improved, especially for fingerprint images.

Set Partitioning in Hierarchical Trees (SPIHT) is a highly efficient technique for compressing Discrete Wavelet Transform (DWT) decomposed images. Though its compression efficiency is a little less famous than Embedded Block Coding with Optimized Truncation (EBCOT) adopted by JPEG2000, SPIHT has a straight forward coding procedure and requires no tables. These make SPIHT a more appropriate algorithm for lower cost hardware implementation. In this paper, a modified SPIHT algorithm is presented. The modifications include a simplification of coefficient scanning process, a 1-D addressing method instead of the original 2-D arrangement of wavelet coefficients, and a fixed memory allocation for the data lists instead of a dynamic allocation approach required in the original SPIHT. Although the distortion is slightly increased, it facilitates an extremely fast throughput and easier hardware implementation. The VLSI implementation demonstrates that the proposed design can encode a CIF (352288) 4:2:0 image sequence with at least 30 frames per second at 100-MHz working frequency.

In this paper, we present a novel energy compaction method, called the selective block-wise reordering, which is used with SPIHT (SBR-SPIHT) coding for low rate video coding to enhance the coding efficiency for motion-compensated residuals. In the proposed coding system, the motion estimation and motion compensation schemes of H.263 are used to reduce the temporal redundancy. The residuals are then wavelet transformed. The block-mapping reorganization utilizes the wavelet zerotree relationship that jointly presents the wavelet coefficients from the lowest subband to high frequency subbands at the same spatial location, and allocates each wavelet tree with all descendents to form a wavelet block. The selective multi-layer block-wise reordering technique is then applied to those wavelet blocks that have energy higher than a threshold to enhance the energy compaction by rearranging the significant pixels in a block to the upper left corner based on the magnitude of energy. An improved SPIHT coding is then applied to each wavelet block, either re-ordered or not. The high energy compaction resulting from the block reordering can reduce the number of redundant bits in the sorting pass and improve the quantization efficiency in the refinement pass of SPIHT coding. Simulation results demonstrate that SBR-SPIHT outperforms H.263 by 1.28-0.69 dB on average for various video sequences at very low bit-rates, ranging from 48 to 10 kbps.