SPIHT Coding Research Articles

Research on image compression technology based on improved SPIHT compression algorithm for power grid data

Abstract At present, the amount of information on power grid operation and maintenance monitoring image data is increasing, and the requirements for data compression are higher and higher. Based on the improved SPIHT image compression algorithm, this study presents the research of power grid data compression. First, the basic theory of image compression, and the principle of one-dimensional wavelet transform and two-dimensional wavelet transform are introduced. The development process, characteristics, and advantages of image coding are discussed. Then, the shortcomings of the SPIHT algorithm are analyzed, and the SPIHT coding is improved by parallel computation. The parallel wavelet transform algorithm based on the block idea and the parallel SPIHT coding algorithm based on the code tree are proposed in the data parallelism of the compression algorithm. At the same time, the data dependence between tasks in the process of SPIHT image compression coding is analyzed, and the task parallelism in the compression algorithm is realized by using the relative independence of tasks in different threshold coding. Finally, the application and simulation analysis of power grid data based on the SPIHT compression algorithm, the construction of power grid data model simulation, and the composition of two-dimensional power grid data images are carried out. Secondly, the obtained 2D power grid data image is compressed by the SPIHT algorithm and improved SPIHT algorithm, respectively, and the compression effect of the two algorithms on the power grid data image is compared. When the bit rate is 0.5, the compression effect of the improved SPIHT algorithm is 13.6506. When the bit rate is 1, the compression effect of the improved SPIHT algorithm is 18.9287. The results show that the improved SPIHT algorithm can compress the grid data to obtain better grid image quality.

Compression of photographic images by the quaternion Wavelet transform associated with SPIHT coding and comparative study with wavelet transform

Compression of photographic images by the quaternion Wavelet transform associated with SPIHT coding and comparative study with wavelet transform

Compressing Face Images Using Genetic and Gray Wolf Meta-heuristic Algorithms Based on Variable Bit Allocation

In image processing, compression plays an important role in monitoring, controlling, and securing the process. The spatial resolution is one of the most effective factors in improving the quality of an image; but, it increases the amount of storage memory required. Based on meta-heuristic algorithms, this article presents a compression model for face images with block division and variable bit allocation. Wavelet transform is used to reduce the dimensions of high spatial resolution face images. In order to identify important and similar areas of identical macroblocks, genetic algorithms and gray wolves are used. A bit rate allocation is calculated for each block to achieve the best recognition accuracy, average PSNR, and SSIM. The CIE and FEI databases have been used as case studies. The proposed method has been tested and compared with the accuracy of image recognition under uncompressed conditions and using the common SPIHT and JPEG coding methods. Recognition accuracy increased from 0.18% for 16×16 blocks to 1.97% for 32×32 blocks. Additionally, the gray wolf algorithm is much faster than the genetic algorithm in reaching the optimal answer. Depending on the application type of the problem, the genetic algorithm or the gray wolf may be preferred to achieve the maximum average PSNR or SSIM. At the bit rate of 0.9, the maximum average PSNR for the gray wolf algorithm is 34.92 and the maximum average SSIM for the genetic algorithm is 0.936. Simulation results indicate that the mentioned algorithms increase PSNR and SSIM by stabilizing or increasing recognition accuracy.

Implementation of FPGA hardware architecture for optimized SPIHT coder using 2DWT-A

Implementation of FPGA hardware architecture for optimized SPIHT coder using 2DWT-A

An Optimized Fragile Image Watermarking Method for Tamper Detection and Recovery Using SPIHT and Reed-Solomon Coding

An Optimized Fragile Image Watermarking Method for Tamper Detection and Recovery Using SPIHT and Reed-Solomon Coding

Medical video compression using bandelet based on lifting scheme and SPIHT coding: In search of high visual quality

Abstract This paper investigates a coding method for medical video compression. The described technique has advantages of providing a higher visual quality of video coding, and efficiently reducing spatial redundancy. Firstly the bandelet transform, also called a non-separable transform, is studied in order to allow an efficient detection of the different complex geometries found in video. After describing the lifting operation in the bandelet transform, we reduced the artifactual effect caused by the quad-tree decomposition step in order to enhance the visual quality of the medical video sequence. Finally, the efficiency of the proposed method on medical video is tested and evaluated by means of a set of objective measurement parameters.

An Improved Downlink MC-CDMA System for Efficient Image Transmission

Image compression is an essential stage of the data archiving and transmitting process, as it reduces the number of bits and the time required to complete the transmission. In this article, a study of image transmission over the Multi-Carrier Code Division Multiple Access (MC-CDMA) downlink system is presented. The solution proposed relies on source coding combined with channel coding. The Discrete Wavelet Transform (DWT) method is used in conjunction with the SPIHT coder to compress the image, then the data generated is transmitted with the MC-CDMA technique over a noisy channel. The results show that image transmissions performed over MC-CDMA using the SPIHT model are better than the traditional approach like MC-CDMA in the AWGN channel.

Three-level parallel-set partitioning in hierarchical trees coding based on the collaborative CPU and GPU for remote sensing images compression

To accelerate the massive remote sensing images (RSIs) coding in a ground service-oriented remote sensing system, this study proposes three-level (i.e., tree-level, bit-plane level, and byte-level) parallel-set partitioning in hierarchical trees (TP-SPIHT) coding on a collaborative central and graphic processing unit (CPU and GPU) to parallelize SPIHT by optimizing its dynamic processing with the linked list. Basic parallel SPIHT coding is presented with preprocessing, tree-level parallel coding, and bit-stream organization using three kinds of static marker matrices instead of the dynamic linked lists originally used to remove the data dependency of the original SPIHT. The bit-stream organization is implemented on CPU and other processes are implemented on GPU using GPU streams. The bit-stream organization is further divided into a bit-plane level parallel bit-plane stream extraction and a final bit-stream organization on a multicore CPU. Because no dependencies exist between the different byte operations in the final bit-stream organization, this organization is accelerated by byte-level parallelization on the GPU. Experimental results with different sized RSIs show that TP-SPIHT takes 292.03 ms to code a 2048×2048 image and achieves a 6.27 times speedup compared with an optimized CPU implementation. The speedup ratio improves as the image increases from 256×256 to 2048×2048.

Video Coding Technique with Multi Objective Particle Swarm Optimization and EZW

Video coding plays an important role in video transmission and storage applications. Today’s increasing order of multimedia applications led to a lot of research works in video coding in such a way that high compression ratio is achieved with the available bandwidth. Wavelet based image compression has witnessed great success in the past decade. Wavelet transform based motion compensated video codec performs better compression in order to meet the rate and distortion constraint in video transmission than the block based techniques. However, it is well known that the 2D DWT does not represent directional features of images efficiently. Lots of efforts have been put into multiscale directional representation. In this paper, video coding using directional transform DDWT is considered and its expansive nature is reduced by noise shaping algorithm. High compression ratio is achieved through the selection of optimal coefficients of DDWT using Multi Objective Particle Swarm Optimization (MOPSO) method. In this video coding technique, the objective functions of Entropy, Computation Time and Mean Square Error are considered for optimization with the constraints of bits per pixel and frame rate. The selected optimum coefficients are encoded using EZW method. The performance of the proposed method is compared with the standard 3D SPIHT coding.

Improving the fingerprint verification performance of set partitioning coders at low bit rates

Wavelet transform combined with the set partitioning coders (SPC) are the most widely used fingerprint image compression approach. Many different SPC coders have been proposed in the literature to encode the wavelet transform coefficients a common feature of which is trying to maximize the global peak-signal-to-noise ratio (PSNR) at a given bit rate. Unfortunately, they have not considered the local variations of SNR within the compressed fingerprint image; therefore, different regions in the compressed image will have different ridge-valley qualities. This problem causes the verification performance to be decreased because minutiae and other useful features cannot be extracted precisely from the low-bit-rate-compressed fingerprint images. Contrast variation within the original image worsens the problem. This paper deals with those applications of fingerprint image compression in which high compression ratios and preserving or improving the verification performance of the compressed images are the main concern. We propose a compression scheme in which the local-SNR (signal-to-noise ratio) variations within the compressed image are minimized (and thus, general quality is maximized everywhere) by means of an iterative procedure. The proposed procedure can be utilized in conjunction with any SPC coder without the need to modify the SPC coder's algorithm. In addition, we used image enhancement to further improve the ridge-valley quality as well as the verification performance of the compressed fingerprint images through alleviating the leakage effect. We evaluated the compression and verification performances of some conventional and modern SPC coders including STW, EZW, SPIHT, WDR, and ASWDR combined with the proposed scheme. This evaluation was performed on the FVC2004 dataset with respect to measures including average PSNR curve versus bit rate, verification accuracy, detection error trade-off (DET) curve, and correlation of matching scores versus the average quality of involved fingerprint images. Simulation results showed considerable improvement on verification performance of all examined SPC coders, especially the SPIHT coder, by using the proposed scheme.

Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding.

In this article, we make a comparative study for a new approach compression between discrete cosine transform (DCT) and discrete wavelet transform (DWT). We seek the transform proper to vector quantization to compress the EMG signals. To do this, we initially associated vector quantization and DCT, then vector quantization and DWT. The coding phase is made by the SPIHT coding (set partitioning in hierarchical trees coding) associated with the arithmetic coding. The method is demonstrated and evaluated on actual EMG data. Objective performance evaluations metrics are presented: compression factor, percentage root mean square difference and signal to noise ratio. The results show that method based on the DWT is more efficient than the method based on the DCT.

A Doubly Error Resilient Coder of Image Sequences

Many scenarios require single frame random access and error resilience in coding, transmission, and decoding of image sequences. We propose in this paper a SPIHT coder that encodes a sequence of images one frame at a time and uses two methods together to achieve strong error resilience. The first method groups wavelet coefficients into a number of tree blocks and the second one encodes these tree blocks independently using SPIHT with progressive significance maps. Because a substantial part of a progressive significance map contains a fixed-length code stream called the complementary significance map (comp-sigmap), transmission bit errors do not propagate within the compsig-map. Furthermore, since the block trees are encoded independently, no error in a given bitstream propagates to another bitstream. Simulations show that the two methods together show stronger error resilience than either one separately. Furthermore, because the groups are formed by interleaved spatial orientation trees, faulty reconstruction from bit errors affecting a given treeblock can be concealed by estimating the true wavelet coefficients from neighboring coefficients in adjacent error-free spatial orien-

Skip block-based wavelet compression for hyperspectral images

Lossy compression methods for hyperspectral image have received a new attention due to the massive amount of information involved for transmission and storage. 3D-SPIHT applies the spatial and spectral correlation on bigger portion of the image for compression which is more complex. This paper proposes a new lossy compression for hyperspectral images, which exploits 8 × 8 block level spectral correlation. A region is identified with more number of 8 × 8 blocks with PSNR greater than 50 db and they are skipped for coding. SPIHT coding is applied for the remaining portion and thereby it effectively utilises the wavelet compression with SPIHT algorithm and the inter band correlation. This new algorithm results in better compression with reduced coding complexity. Results show that skip block-based scheme retains all the desirable features of compared state-of-the-art algorithms and is highly competitive to 3D-SPIHT and better than 2D-SPIHT in compression efficiency.

Analysis and Comparison of EZW, SPIHT and EBCOT Coding Schemes with Reduced Execution Time

In the digital era of communication it is very common to sending some information from one point to another. In every field of engineering that is biomedical, astronomical, geological etc. Image is one of the commonly used multimedia. So for fast and efficient communication formulate, image compression is needed in each and every field. Intended for coding of transformed image, here is a comparison between various parameters of three of coding schemes EZW, SPIHT and EBCOT. After the transformation, those coding scheme basically code high energy components first and progressively transmits the coded bits to make an increasingly update and refined copy of the original image. In this paper reduced the execution time and provide the best reconstructed image with higher PSNR by using those coding schemes. The compared results of various parameters of image compression algorithms analyzed using MATLAB software and wavelet toolbox.

Study on Compressing Data for Three-Phase Power Based on Adaptive Two-Dimensional Wavelet Packet

This paper presents a method based on adaptive two-dimensional wavelet packet for three-phase power quality data. In this paper, we shall briefly introduce the method of dq0 transformation. First, the original data is converted by the method of dq0 transformation, its purpose may be to eliminate redundancy between the three-phases alternating data, then change the one-dimensional date converted into a two-dimensional matrix by the integral multiple of cycles, which aims to eliminate redundant between cycles. Finally, use the method of two-dimensional adaptive wavelet packet decomposition, image SPIHT coding and DEFLATE coding to compress the data. The simulation result shows that the algorithm effectively compress the three-phase power quality data, and it has a good compression effect.

An Effective Selection of DCT and DWT Coefficients for an Adaptive Medical Image Compression Technique Using Multiple Kernel FCM

Over the last two decades, great developments have been made in image compression approaches driven by a growing demand for storage and transmission of visual information. However, a number of publications have demonstrated good results of the compressed domain approach to image analysis. Nevertheless, very little work has been carried out on ROI based compression. In this paper, we have proposed an adaptive approach to compress the image without lossless version using selection of DCT and DWT coefficients and MKFCM. Our proposed approach consists of three stages, (i) Region segmentation (ii) Image compression (iii) Image decompression. At first, the input medical image is segmented by ROI, Non-ROI and background using MKFCM. Subsequently, the ROI region compressed by DCT and SPIHT coding and Non-ROI region is compressed by DWT and Huffman coding. The non-relevant regions are directly converted to zero. From the compressed regions like as ROI, Non-ROI and background, finally we obtain compression ratio to evaluate the proposed approach. Then, in decompression stage, the original medical image is extracted using the devised procedure. We can also see that our proposed image compression approach have outperformed by having better compression ratio of 4.6446 when compared existing technique only achieved 4.4326

The Performance of Discret Bandelet Transform Coupled by SPIHT Coder to Improve the Visuel Quality of Biomedical Color Image Compression

The search for a good representation is a central problem of image processing, this paper explores a new transform type to solve this problem. Color Image compression is now essential for applications such as transmission and storage in data. In the field of medical diagnostics, interested parties have resorted increasingly to color medical imaging. It is well established that the accuracy and completeness of diagnosis are initially connected with the image quality. This paper introduces an algorithm for color medical image compression based on the bandelet transform coupled with SPI HT coding algorithm;bandelet transform is a new method based on capturing the complex geometric content in image. The goal of this paper is to examine the capacity of this transform proposed to offer an optimal representation for image geometric, In order to enhance the compression by our algorithm, we have compared the results obtained with bandelet transform application in satellite image field. For this reason, we evaluated two parameters known for their calculation speed. The first parameter is the PSNR; the second is MSSIM (structural similarity) to measure the quality of compressed image. We concluded that the results obtained are very satisfactory for color medical image domain

A lossless DEM compression for fast retrieval method using fuzzy clustering and MANFIS neural network

In this paper, we propose an integrated approach between fuzzy C-means (FCM) and multi-active neuro fuzzy inference system (MANFIS) for the lossless DEM compression for fast retrieval (DCR) problem, aiming to compress digital elevation model (DEM) data with the priority of fast retrieval from the client machine over the Internet environment. Previous researches of this problem either used the float wavelet transforms integrated with the SPIHT coding or constructed a predictor model using statistical correlation of DEM data in local neighborhoods; thus giving large-sized compressed data and slow transferring time of data between the server and the client. Based on the observation that different non-linear transforms for predictive values in the sliding windows may increase the compression ratio, we herein present a novel approach for DCR problem and validated it experimentally on the benchmark DEM datasets. The comparative results show that our method produces better compression ratio than the relevant ones.

A Comparative Study between Bandelet and Wavelet Transform Coupled by EZW and SPIHT Coder for Image Compression

Second generation bandelet transform is a new method based on capturing the complex geo metric content in image; we use this transform to study medical and satellite image co mpressed using the bandelet transform coupled by SPIHT coder. The goal of this paper is to examine the capacity of this transform proposed to offer an optimal representation for image geometric. We are interested in co mpressed medical image, In order to develop the compressed algorithm we compared our results with those obtained by the bandelet transform application in satellite image field. We concluded that the results obtained are very satisfactory for med ical image do main.

VIDEO CODING TECHNIQUE USING 3D DUALTREE DISCRETE WAVELET TRANSFORM WITH MULTI OBJECTIVE PARTICLE SWARM OPTIMIZATION APPROACHES

Wavelet-based image compression with Wavelet transform based motion compensated video codec performs better compression to meet the rate and distortion constraints in video transmission with the available bandwidth than the block based techniques. However, it is well known that the 2D DWT does not represent directional features of images efficiently. Lots of efforts have been contributed to multiscale directional representation. In this study Video coding using Dualtree Discrete Wavelet Transform is considered and its expansive nature is reduced by noise shaping algorithm and high compression ratio is achieved by means of the selection of optimal coefficients using MOPSO method. In Multiobjective Optimization (MO) problems, more than one objective functions have to be minimized simultaneously. In the proposed method, Entropy of the sub bands and Mean square error are considered for optimization with the constraints of frame rate. The two different types of MOPSO approaches such as weighted aggregation approach and Vector Evaluated PSO are used to select the optimum subbands. The two techniques outputs are compared with the standard 3D SPIHT coding.