A Survey of Image Compression Algorithms for Visual Sensor Networks <s> SPIHT Background. SPIHT introduced in <s> Embedded zerotree wavelet (EZW) coding, introduced by Shapiro (see IEEE Trans. Signal Processing, vol.41, no.12, p.3445, 1993), is a very effective and computationally simple technique for image compression. We offer an alternative explanation of the principles of its operation, so that the reasons for its excellent performance can be better understood. These principles are partial ordering by magnitude with a set partitioning sorting algorithm, ordered bit plane transmission, and exploitation of self-similarity across different scales of an image wavelet transform. Moreover, we present a new and different implementation based on set partitioning in hierarchical trees (SPIHT), which provides even better performance than our previously reported extension of EZW that surpassed the performance of the original EZW. The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods. In addition, the new coding and decoding procedures are extremely fast, and they can be made even faster, with only small loss in performance, by omitting entropy coding of the bit stream by the arithmetic code. <s> BIB001 </s> A Survey of Image Compression Algorithms for Visual Sensor Networks <s> SPIHT Background. SPIHT introduced in <s> Two well-known wavelet zerotree encoding algorithms, Embedded Zerotree Encoding (Ezw) and Set Partitioning in Hierarchical Trees (Spiht), provide excellent progressive display when images are transmitted over reliable networks. However, both algorithms are state-dependent and can perform poorly over unreliable networks. We apply the concept of network-conscious image compression to theSpiht wavelet zerotree encoding algorithm, to improve its performance over unreliable networks. Experimental results confirm the utility of network-conscious image compression concept. <s> BIB002 </s> A Survey of Image Compression Algorithms for Visual Sensor Networks <s> SPIHT Background. SPIHT introduced in <s> Among all algorithms based on wavelet transform and zerotree quantization, Said and Pearlman's (1996) set partitioning in hierarchical trees (SPIHT) algorithm is well-known for its simplicity and efficiency. This paper deals with the real-time implementation of SPIHT algorithm using DSP chip. In order to facilitate the implementation and improve the codec's performance, some relative issues are thoroughly discussed, such as the optimization of program structure to speed up the wavelet decomposition. SPIHT's high memory requirement is a major drawback for hardware implementation. In this paper, we modify the original SPIHT algorithm by presenting two new concepts-number of error bits and absolute zerotree. Consequently, the memory cost is significantly reduced. We also introduce a new method to control the coding process by number of error bits. Our experimental results show that the implementation meets common requirement of real-time video coding and is proven to be a practical and efficient DSP solution. <s> BIB003 </s> A Survey of Image Compression Algorithms for Visual Sensor Networks <s> SPIHT Background. SPIHT introduced in <s> Among all algorithms based on wavelet transform and zerotree quantization, Said and Pearlman’s set partitioning in hierarchical trees (SPIHT) algorithm is well known for its simplicity and efficiency. SPIHT’s high memory requirement is a major drawback to hardware implementation. In this study, we present a modification of SPIHT named modified SPIHT (MSPIHT), which requires less execution time at a low bit rate and less working memory than SPIHT. The MSPIHT coding algorithm is modified with the use of one list to store the coordinates of wavelet coefficients instead of three lists of SPIHT; defines two terms, number of error bits and absolute zerotree; and merges the sorting pass and the refinement pass together as one scan pass. Comparison of MSPIHT with SPIHT on different test image shows that MSPIHT reduces execution time at most 7 times for coding a 512 × 512 grayscale image; reduces execution time at most 11 times at a low bit rate; saves at least 0.5625 MB of memory; and reduces minor peak signal-to noise ratio (PSNR) values, thereby making it highly promising for real-time and memory limited mobile communications. <s> BIB004
SPIHT achieves very compact output bitstream and low bit rate than that of its predecessor's EZW without adding an entropy encoder, which allows its efficiency in terms of computational complexity BIB001 . Moreover, it uses a subset partitioning scheme in the sorting pass to reduce the number of magnitude comparisons, which also decrease the computational complexity of the algorithm. Finally, the progressive mode of SPIHT allows the interruption of coding/decoding process at any stage of the compression BIB001 . Despite these advantages, SPIHT presents the following shortcomings, particularly in power-constrained applications. It requires important memory storage and sorting/list procedures, which increases the complexity and the computational complexity. Precisely, SPIHT uses three lists to store coding information which needs large memory storage. In general, those lists grow up with the encoding process, which requires additional memory. Furthermore, the wavelet filter used in SPIHT is Mallat algorithm based, which incurs large convolution computations compared to lifting scheme version of wavelet transforms. As with EZW, over unreliable networks, SPIHT suffers from the network state and, thus, is vulnerable against packets loss, which requires the use of an appropriate error correction scheme. Many attempts to enhance SPIHT features and reduce its limitations have been suggested in the literature, for instance BIB002 BIB003 BIB004 . In BIB002 , the authors apply the concept of networkconscious image compression to the SPIHT algorithm to improve its performance under lossy conditions. Hence, SPIHT-NC (a network-conscious version of SPIHT) is suggested to enhance its performance over unreliable networks. A real-time implementation of SPIHT is presented in BIB003 . The authors try to speed up the SPIHT process and reduce the internal memory usage by optimizing the program structure and presenting two concept numbers of error bits and absolute zerotree. An improved zerotree structure and a new coding procedure are adopted in BIB003 to improve the quality of the reconstructed image by SPIHT. To further reduce the internal memory usage, the authors suggest a listless version of SPIHT, where lists are replaced successfully by flag maps. Moreover, a wavelet lifting scheme is adopted to speed up the coding process. A modified SPIHT algorithm for realtime image compression, which requires less execution time and less memory usage than SPIHT, is presented in BIB004 . Instead of three lists, the authors use merely one list to store the coordinates of wavelet coefficients, and they merge the sorting pass and the refinement pass together as one scan pass.