A Modified SPIHT Algorithm Based on Wavelet Coefficient Blocks for Robust Image Transmission over Noisy Channel

In view of increasing use of video transmission over wireless channels, a lot of research efforts have been made to trade-off the error resiliency and transmission bandwidth requirements. This in turn has led to development of various unequal error protection (UEP) schemes. In this paper, the performance of optimized 2-layered and 3-layered UEP schemes using hierarchical 64 QAM (64-HQAM) for wavelet-transformed images coded with set partitioning in hierarchical trees (SPIHT) algorithm and transmitted over additive white Gaussian noise (AWGN) channel is investigated. A look-up table (LUT) based approach to select the optimal values of modulation parameters of 64-HQAM for different channel conditions is suggested so as to reduce the computational complexity. Simulation results show that 3-layered optimized 64-HQAM-based UEP outperforms corresponding non-optimized UEP. Also, 3-layered optimized UEP scheme using 64-HQAM performs slightly better as compared to optimized 2-layered UEP scheme using 64-HQAM.

Transform coding has been the focus of the research for image compression. In previous research, the Amplitude and Group Partitioning (AGP) coding scheme is proved to be a low complexity algorithm with higher performance, clearly one of the state-of-art transform coding techniques. However, the previous AGP is used along with the Discrete Cosine Transform (DCT) and the discrete wavelet transform. In this paper, a different transform, the Lapped Orthogonal Transform (LOT), replaces the DCT in conjunction with the AGP. This is the first time LOT and AGP have been combined in a coding method. The definition and design of the LOT are discussed. An objective metric to measure the performance of transform, coding gain, is calculated for both the DCT and the LOT. The LOT has slightly higher coding gain than the DCT. The principles of the LOT based AGP image codec (LOT-AGP) are presented and a complete codec, encoder and decoder, is implemented in software. The performance of the LOT-AGP is compared with other block transform coding schemes: the baseline JPEG codec and the DCT based AGP image codec (DCT- AGP) by both objective evaluation and subjective evaluation. The Peak Signal to Noise Ratio (PSNR) is calculated for these three coding schemes. The two AGP codecs are much better than the JPEG codec on PSNR, from about 1.7 dB to 3 dB depending on bit rate. The two AGP schemes have PSNR differences only to a small degree. Visually, the LOT-AGP has the best-reconstructed images among these three at all bit rates. In addition, the coding results of two other state-of-art progressive image codecs are cited for further comparison. One is the Set Partitioning in Hierarchical Trees (SPIHT) algorithm with a dyadic wavelet transform, and the other is Tran and Nguyen's method with the generalized LOT transform. The AGP coding and the adaptive Huffman entropy coding of LOT-AGP are less complex and the memory usage is smaller than in these two progressive codecs. Comparing these three codecs, i.e. the LOT-AGP and the two progressive codecs in PSNR small only small differences in PSNR. SPIHT has about 1 dB higher PSNR than the LOT-AGP and Tran and Nguyen's method for the test image Lena. For the test image Barbara, the PSNR of the LOT- AGP is about 0.5 dB higher than that of the SPIHT and 0.5 dB lower than that of Tran and Nguyen's method. This low- complexity and high performance codec may provide a new direction for the implementation of image compression.

Set Partitioning in Hierarchical Trees (SPIHT) is an effective image compression algorithm. SPIHT is a unique approach which transmits the values of the pixels indirectly to the coordinates. The packet coders in the images present a universal transform the framework in a constriction of the filter bank schema which is attained by the Space Frequency Quantization (SFQ) and the effective compression is achieved by the Huffman coding. The proposed scheme permits transformation in the joints and alterations in the discrete magnitude of the input image. Hence, coding performance is enhanced and the image is compressed without compromising the excellence of the image. MSPIHT is an enhanced algorithm that fits the requirement of medical image compression for storage and transmission of medical data. MSPIHT improves on the standard SPIHT in the encoding operation of wavelet coefficients to provide high quality images at low bit rates important in medical applications where accuracy is paramount. The modification is aimed at changing the set partitioning strategy by minimizing memory consumption rates, thus improving the compression ratio and speed. It also may be used at telemedicine where high image compression rate is required for the quick and efficient image transfer for diagnostics and consultations. Experimental results shows that the image compression scheme is improved with the SPIHT-SFQ based Huffman Coding scheme and it outperforms the current image compression algorithms.

The recent innovation in digital medical imaging techniques requires the development of high-performance storage and image transmission systems. The biggest problem in digital technology is voluminous amount of data generated. For example, a digital mammographic image of size 1024 × 1024 pixels with 8 bits per pixel requires 8.3 Mb for storing it in original form. Researchers in several studies have demonstrated the need for high rate compression algorithms for medical imaging applications. But the recently reported image compression results indicate that Peak Signal-to-Noise Ratio (PSNR) is outperformed by scalar wavelets. However, it often fails to capture high-frequency information accurately. Interestingly, multiwavelet preserves high-frequency information in mammographic image and provides good energy compaction. The challenge still remains as to how one can better represent the signal for achieving the best compression. This paper proposes a solution to the above open problems using balanced multiwavelet-based image compression. The proposed scheme presents combination of two novel ideas: A coefficient reorganization suitable to balanced multiwavelet decomposition is used to regain the parent-child relationship. A block tree coding is used for compression and reconstruction of multiwavelet transformed image and thus the proposed scheme is called as Multiwavelet Block Tree Coding (MBTC). This approach yields the advantages of high energy compaction, PSNR, and a less number of bits for encoding. Balanced multiwavelet-based compression, with MBTC applied to a set of four mammographic images, achieves an average PSNR of 43.245 dB against the existing Set Partitioning In Hierarchical Trees (SPIHT) algorithm which on an average achieves only 34.181 dB for 0.5 bpp bit rate and MBTC requires encoding bits of 45.565% less than SPIHT encoding.

Medical images must be compressed before transmission due to bandwidth and storage limitations. The set partitioning in hierar- chical trees (SPIHT) algorithm is an efficient method for lossy and loss- less coding of medical images. We propose some modifications to the SPIHT algorithm. It is based on the idea of the insignificant correlation of wavelet coefficients among medium- and high-frequency subbands. In this scheme, insignificant wavelet coefficients that correspond to the same spatial location in the medium subbands can be used to reduce the redundancy by a combined function proposed in associated with the modified SPIHT. In high-frequency subbands, the modified SPIHT pro- poses a dictator to reduce the interband redundancy. Experimental re- sults indicate that the proposed technique improves the quality of the reconstructed medical image in terms of both the peak signal-to-noise ratio (PSNR) and the perceptual results over JPEG2000 and the original SPIHT at the same bit rate. © 2003 Society of Photo-Optical Instrumentation Engi- neers. (DOI: 10.1117/1.1578645)

We have considered, in this paper, two compression methods based on wavelet transform and progressive coding, called EZW (Embedded Zerotree Wavelet) and SPIHT (Set partitioning in hierarchical trees). These techniques provide the opportunity to significantly increase compression ratios while preserving high qualities of reconstructed medical images. Unlike the EZW, the SPIHT approach takes advantage of subband correlations at near and far resolution levels (father-son relationships). A partial ordering by amplitude of the wavelet coefficients of the DWT (Discrete Wavelet Transform), partitioning in hierarchical trees, and scheduling of the transmission of the refinement bits are the three ideas used by SPIHT (the amplitude of each significant coefficient is progressively refined). The goal is to create a digital tool with the required main compression rate and PSNR (Peak Signal to Noise Ratio) limitations for compressing medical images. A development of the two cited algorithms has been carried out. For their evaluation, several medical images from two databases were used. The results prove that these algorithms are very efficient. Also, it has been found that the obtained results with SPIHT method greatly exceed those provided by EZW approach. SPIHT approach is very efficient compared to EZW from the point of view of the compression ratio and the image quality.

In this paper, a power water-filling scheme for unequal error protection (UEP) based on set partitioning in hierarchical trees (SPIHT) coded image transmission over multiple input multiple output(MIMO) channels is proposed. SPIHT coded image information is divided into different sub-streams according to their different importance, which is allocated to different channels. Then unequal error protection (UEP) of image with singular value decomposition and power water-filling policy is achieved. The simulation results show that the quality of reconstructed image of using UEP is better than equal error protection (EEP).

Image compression is an important task for image transmission and storage. Thus far many compression techniques have been developed, such as transform image coding, predictive image coding, Vector Quantisation (VQ) and so on. Of these compression techniques, the techniques based on transform coding and VQ have received considerable attention. Recently, hybrid schemes for effective image compression have gained enormous popularity among researchers. In this paper, we analyse a hybrid scheme combining Kohonen’s Self-Organising Feature Map (SOFM)-based VQ coding and Set Partitioning In Hierarchical Trees (SPIHT) coding for compression of images (Rawat and Meher, 2009). The reconstructed image quality achieved after decoding depends upon the wavelet used in SPIHT. The effectiveness of the scheme for various orthogonal and biorthogonal wavelets for the hybrid scheme is tested in terms of Peak Signal-to-Noise Ratio (PSNR) and Visual Information Fidelity (VIF).

This paper describes applying the Set Partitioning in Hierarchical Trees (SPIHT) algorithm using a devised model to compress audio signals. It allows choosing the amount of compression based upon bit rate requirements. A threshold setting model, based on energy and frequency patterns of the signal is used to assist the SPIHT encoder set efficient threshold values, based upon the nature of the audio. It is thus adaptable to the nature of the audio as well as the bit rate requirement. The implementation can be used for storage as well as progressive transmission.

In this paper, a new multiple description coding (MDC) method for color images is presented. The proposed approach bases on the set partitioning in hierarchical trees (SPIHT) algorithm to achieve a high image compression ratio; employs poly-phase sampling technique to generate multiple descriptions to adapt to varying internet environments. It results in having capabilities to conquer packet losses and remaining the reconstructed images with an acceptable quality. In order to preserve the progressive reconstruction properties for a color image transmission, the three components (Red, Green, and Blue) are encoded separately and their encoding results are interleaved for transmission. The proposed method is applicable to color images and is very flexible for practical applications. The experimental results are given to illustrate the characteristics and verify the efficiency of the proposed method.

To prolong the life cycle of wireless sensor network, the basic theory of wavelet transform and its application in image compression are described, and several classic image compression algorithms based on wavelet transform are studied in depth. A compression algorithm combining the improved wavelet transform and Set Partitioning in Hierarchical Trees (SPIHT) algorithm of hierarchical wavelet tree set segmentation is proposed to effectively balance the energy consumption of each node in the sensor network and prolong the life of the whole wireless sensor network and an improved distributed image compression and transmission algorithm is proposed based on the distributed multi-node cooperative processing algorithm based on wavelet transformation, and detailed analytical test and energy consumption simulation experiment are carried out to verify the feasibility of the algorithm. The results show that the platform effectively implements and verifies the proposed algorithm, which can effectively realize the compression and transmission of distributed images, equalize the energy consumption of each sensor node in the network, and has strong practicability.

Set partitioning in hierarchical trees (SPIHT) image compression algorithm based on wavelet transform can't effectively express the image of the texture and contour. Contourlet transform can retain image details better because it avoids down sampling to high-frequency subband, and the coefficient is also sparser than it of wavelet transform. In this paper, a suitable SPIHT algorithm for contourlet transform was proposed for its coefficient matrix characteristics and distribution. The new algorithm not only overcome the disadvantage of not protecting details and texture effectively when using wavelet transform, but also saves coding time, at the same time enhance the image of the peak signal to noise ratio (PSNR). Simulation results show that the method is an efficient image compression algorithm. Its compression effect is obviously better than traditional SPIHT algorithms based on wavelet transform and WBCT (especially at low bit rates). It has generality.

In this paper, we present a multiple hierarchical coding and transmission scheme in which both the fragile structure of set partitioning in hierarchical trees (SPIHT) source coding and the unequal importance of bits in the coded bitstream have been taken into account. Multiple subsampling is applied to split the wavelet coeffcients of the original image source into multiple subsources so that each subsource is a crude representation of the original image. The sequential dependence of coded bitstream is broken. As a result, the error propagation is limited to a single subsource which is also coded with SPIHT to achieve desired coding performance. Cyclic redundancy coder/rate compatible punctured convolutional coder (CRC/RCPC) channel coding has been used to offer unequal error protection (UEP) to the multiple coded bitstreams. In each substream all the bits in the same bit layer are protected with the same channel code. The higher the bit-layer, the more the channel coding protects. Experimented results show that this new scheme has a good error resilient performance over wireless channels with time varying and bursty errors characteristics. In particular the reconstructed images often demonstrate good visual quality.

We extend the work of Sherwood and Zeger to progressive video coding for noisy channels. By utilizing a 3D extension of the set partitioning in hierarchical trees (SPIHT) algorithm, we cascade the resulting 3D SPIHT video coder with a rate-compatible punctured convolutional channel coder for transmission of video over a binary symmetric channel. Progressive coding is achieved by increasing the target rate of the 3D embedded SPIHT video coder as the channel condition improves. The performance of our proposed coding system is acceptable at low transmission rate and bad channel conditions. Its low complexity makes it suitable for emerging applications such as video over wireless channels.

We investigate the issue of efficient data organization and representation of the curved wavelet coefficients [curved wavelet transform (WT)]. We present an adaptive zero-tree structure that exploits the cross-subband similarity of the curved wavelet transform. In the embedded zero-tree wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT), the parent-child relationship is defined in such a way that a parent has four children, restricted to a square of 2×2 pixels, the parent-child relationship in the adaptive zero-tree structure varies according to the curves along which the curved WT is performed. Five child patterns were determined based on different combinations of curve orientation. A new image coder was then developed based on this adaptive zero-tree structure and the set-partitioning technique. Experimental results using synthetic and natural images showed the effectiveness of the proposed adaptive zero-tree structure for encoding of the curved wavelet coefficients. The coding gain of the proposed coder can be up to 1.2 dB in terms of peak SNR (PSNR) compared to the SPIHT coder. Subjective evaluation shows that the proposed coder preserves lines and edges better than the SPIHT coder.