Ranjan K. Senapati

Reduced memory, low complexity embedded image compression algorithm using hierarchical listless discrete tchebichef transform

Listless set partitioning embedded block (LSK) and set partitioning embedded block (SPECK) are known for their low complexity and simple implementation. However, the drawback is that these block-based algorithms encode each insignificant subband by a zero. This generates many zeros at earlier passes because the number of significant coefficients at higher bitplanes is likely to be very few in a transformed image. An improved LSK (ILSK) algorithm that codes a single zero to several insignificant subbands is proposed. This reduces the length of the output bit string, encoding/decoding time and dynamic memory requirement at early passes. Furthermore, ILSK algorithm is coupled with discrete Tchebichef transform (DTT). This gives rise to a novel coder named as hierarchical listless DTT (HLDTT). The proposed HLDTT has desirable attributes like full embeddedness for progressive transmission, precise rate control for constant bit rate traffic and low complexity for low power applications. The performance of HLDTT is assessed using peak-signal-to-noise-ratio (PSNR) and structural-similarity-index-metric (SSIM). Extensive simulation conducted on various standard test images shows that HLDTT exhibits significant improvement in PSNR values from lower to medium bit rates. At the same time, HLDTT shows improvement in SSIM values on all bit rates.

A low complexity orthogonal 8×8 transform matrix for fast image compression

In this paper, an efficient orthogonal sparse 8×8 transform matrix for low bit-rate image compression is proposed. The transform matrix is made sparse by appropriately inserting additional zeros into the matrix proposed by Bouguezel. The algorithm for fast computation is also developed. It is shown that the proposed transform matrix provides a 20% reduction in computation over the matrix proposed by Bouguezel, and 45% over signed discrete cosine transform (SDCT). By using various test images, it is shown that the rate-distortion performance is also almost comparable to that of above two transform matrices at low bit-rates.

A low complexity embedded image coding algorithm using Hierarchical Listless DTT

Listless SPECK (LSPECK) is a low complexity image coding algorithm compared to SPECK. The problem of LSPECK is that, it encode each insignificant subband by a zero. Therefore, these block based coders codes as many zeros as the number of insignificant subbands. This gives rise to many zeros at the encoder output on early bit plane passes. By looking at the statistics of transformed images, the number of significant coefficients at some of the higher bitplanes are likely to be very few. We propose a variant of LSPECK algorithm, called as Improved LSPECK (ILSPECK), that code a single zero to several insignificant subbands. This reduces the length of the output bit string as well as encoding/decoding time. Further, ILSPECK algorithm is coupled with discrete tchebichef transform (DTT). The propose new coder called as Hierarchical Listless DTT (HLDTT), preserves most of the properties of wavelet coders. Extensive simulations on various kind of images shows the effictiveness of our coder.

Image Compression Using Discrete Tchebichef Transform Algorithm

The Discrete Tchebichef Transform (DTT) based on orthogonal Tchebichef polynomials can be an alternative to Discrete Cosine Transform (DCT) for JPEG image compression standard. The properties of DTT are not only very similar to DCT; it has also higher energy compactness and lower computational advantage using a set of recurrence relation. Through extensive simulation, image reconstruction accuracy (Peak Signal to Noise Ratio) and the number of bits required to encode the coefficients for both DCT and DTT is verified. It has been demonstrated that, DTT requires lesser number of bits to encode the coefficients than DCT for a given compression ratio.

Improved Listless Embedded Block Partitioning Algorithms for Image Compression

In this paper, two simple yet efficient embedded block-based image compression algorithms are presented. These algorithms not only improve the rate distortion performances of set partitioning in hierarchical trees (SPIHT) and set partitioning in embedded block coder (SPECK) at lower bit rates but also reduces the dynamic memory requirement by 91.1% in comparison to SPIHT. The former objective is achieved by better exploiting the coefficient decaying spectrum of the wavelet transformd images and the later objective is realised by improved listless implementation of the algorithms. The proposed algorithms explicitly perform breadth first search like SPECK. Extensive simulation conducted on various standard grayscale and color images indicate significant peak-signal-to-noise-ratio (PSNR) improvement over most of the state-of-the-art wavelet-based embedded coders including JPEG2000 at lower rates. The reduction of encoding and decoding time as well as improvement in coding efficiency at lower bit rates facilitate these coder as better candidates for multimedia applications.

LOW BIT RATE IMAGE COMPRESSION USING HIERARCHICAL LISTLESS BLOCK-TREE DTT ALGORITHM

This paper presents a listless variant of modified wavelet block tree coding (MLBTC) algorithm. Wavelet block-tree coding (WBTC) improves the image compression performance of set partitioning in hierarchical trees (SPIHT) at lower rates by efficiently encoding both inter- and intra-scale correlations. The use of auxiliary lists makes WBTC undesirable for hardware implementation as it needs a lot of memory management due to exponential increase of nodes on each pass. The proposed coder named as hierarchical listless block-tree DTT (HLBT_DTT) that combines discrete Tchebichef transform (DTT) with MLBTC exhibits compression performance significantly higher than most of the DCT-based embedded coders and comparable with JPEG 2000, especially at lower bit rates. Further, HLBT_DTT requires only 10% of memory than that of DCT-based SPIHT/WBTC coders.

A Novel Hybrid HVS Based Embedded Imagecoding Algorithm Using DTT and SPIHT

This paper presents a Discrete Tchebichef Transform (DTT) based hybrid embedded coder for image compression applications. In this coder, DTT is coupled with Set partitioning in hierarchical coding techniques (SPIHT). Further, human visual system (HVS) with appropriate perceptual weights are applied to improve the perceptual quality of the reconstructed image. The compression and image reconstructon performance is compared with some the state-of-the-art coders in the literature. Extensive simulations on various kinds of images shows convincingly that,the proposed coder outperforms most of the coders.

A Novel Fast Zigzag Prune 4×4 Discrete Tchebichef Moment Based Image Compression Algorithm

The Discrete Tchebichef Moment (DTM) is a linear orthogonal transform which has higher energy compactness property like other orthogonal transform. It is recently found applications in image analysis and compression. This paper proposes a new approach of fast zigzag pruning algorithm of 4x4 DTM coefficients. The principal ideal of the proposed algorithm is to make use of the distributed arithmetic and the symmetry property of 2-D DTM, which combines the similar terms of the pruned output. The multiplication terms are replaced by shift and add operations so as to reduce the computation. Equal number of zigzag pruned coefficients and block pruned coefficients are used for comparison to test the efficiency of our algorithm. Experimental method shows that our method is competitive with the block pruned method. Specifically for 3x3 block pruned case our method provides lesser computational complexity and has higher peak signal to noise ratio (PSNR).

An efficient sparse 8 × 8 orthogonal transform matrix for colour image compression

This paper presents an efficient orthogonal sparse 8 × 8 transform matrix for colour image compression particularly at lower bit rate applications. The transform matrix implemented in Xilinx XC2VP30 FPGA device indicates that a significant saving in computation and hardware resources over Discrete Cosine Transform (DCT), Signed Discrete Cosine Transform (SDCT), approximate DCT and matrix proposed by Bouguezel. By using various natural test images, it is demonstrated that the subjective and objective qualities are comparable with the above–mentioned transforms at lower bit rates. Furthermore, it outperforms SDCT by a large margin almost at all bit rates for most of the images.