Modified set partitioning in hierarchical trees algorithm based on hierarchical subbands

Abstract

Abstract. This paper introduces a modified set partitioning in hierarchical trees (SPIHT) algorithm that reduces the number of comparison operations and, consequently, the execution time needed to encode an image as compared to the SPIHT algorithm. The threshold of each independent subband is calculated after applying the discrete wavelet transform to the image. Scanning of the sets inside the subbands is determined by the magnitude of the thresholds that establishes a hierarchical scanning not only for the set of coefficients with larger magnitude, but also for the subbands. The algorithm uses the set partitioning technique to sort the transform coefficients. Results show that the modified SPIHT significantly reduces the number of operations and the execution time without sacrificing visual quality and the PSNR of the recovered image. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

A Simple and Fast Algorithm for Image Coding Based on SPIHT

“…The performance of the proposed modified SPIHT is examined and compared with SPIHT and Domínguez et al [20] (with good coding speed, the source code is provided by the author) methods using the images of Lena, Peppers, and Goldhill at monochrome 512 × 512 size. In the experiment, each image is decomposed by using CDF 9/7 filter bank with 6 level (L = 6).…”

“…Note: Black fonts indicate the best performance. Table 1 shows the numerical results of the execution time of the modified SPIHT, compared with SPIHT and Domínguez et al [20] methods for the Lena, Peppers, and Goldhill images. The time performance of the modified SPIHT at each bit rate listed in table 1 is the most superior.…”

“…Domínguez at al. [20] combines the SPIHT lists and hierarchical subband scanning to save comparison operations during sorting passes, which drastically reducing the time taken by the encoder per sorting pass. However, this algorithm is based on complex SOT structure which must discriminate if a set contains significant pixels, consuming time.…”

“…This balances the performance of a code and improves the efficiency of coding. Domínguez et al [20] combines the SPIHT lists and hierarchical subband scanning to save comparison operations during sorting passes. The sets inside a subband are scanned according to the magnitude of its subband threshold.…”