REMOTE SENSING IMAGE CODING METHOD COMBINING WAVELET TRANSFORM WITH CLASSIFIED VECTOR QUANTIZATION

A new remote sensing image coding scheme based on the wavelet transform and classified vector quantization (CVQ) is proposed. The original image is first decomposed into a hierarchy of 3 layers including 10 subimages by DWT. The lowest frequency subimage is compressed by scalar quantization and ADPCM. The high frequency subimages are compressed by CVQ to utilize the similarity among different resolutions while improving the edge quality and reducing computational complexity. The experimental results show that the proposed scheme has a better performance than JPEG, and a PSNR of reconstructed image is 31～33 dB with a rate of 0.2 bpp.

Efficient Quadtree based Fractal Image Coding Scheme in Wavelet Transform Domain *

This paper presents an efficient quadtree based fractal image coding scheme in wavelet transform domain based on the wavelet based theory of fractal image compression introduced by Davis. In the scheme, zerotrees of wavelet coefficients are used to reduce the number of domain blocks, which leads to lower bit cost required to represent the location information of fractal coding, and overall entropy constrained optimization is performed for the decision trees as well as for the sets of scalar quantizers and self quantizers of wavelet subtrees. Experiment results show that at the low bit rates, the proposed scheme gives about 1 dB improvement in PSNR over the reported results.

A Novel Coding Method Based on Fuzzy Vector Quantization for Noised Image

In this paper a novel coding method based on fuzzy vector quantization for noised image with Gaussian white-noise pollution is presented. By restraining the high frequency subbands of wavelet image the noise is significantly removed and coded with fuzzy vector quantization. The experimental result shows that the method can not only achieve high compression ratio but also remove noise dramatically.

METHOD OF VECTOR QUANTIZATION CODING USING RECTANGULAR TRANSFORM FOR IMAGE COMPRESSION

First of all a simple and practical rectangular transform is given,and then thevector quantization technique which is rapidly developing recently is introduced.We combinethe rectangular transform with vector quantization technique for image data compression.Thecombination cuts down the dimensions of vector coding.The size of the codebook can reasonablybe reduced.This method can reduce the computation complexity and pick up the vector codingprocess.Experiments using image processing system show that this method is very effective inthe field of image data compression.

Fabric Defect Detection Using Adaptive Wavelet Transform

A method of woven fabric defect detection using the wavelet transform adaptive to the fabric has been developed. With reference to the orthogonality constrains of Daubechies wavelet, by taking the mmimization of the energy or the gray level of the pixels in the output sub-images as the additional conditions and using the random algorithm method, two sets of wavelet filters adapted to the fabric texture were formed. The original images of normal fabric texture and the fabric texture with defects were decomposed into horizontal and vertical sub- images by using these filters and the feature indices of these sub-images were also extracted. By comparing the feature indices of the normal texture with that of the defective texture, the fabric defects can be successfully detected and located.

Blind and readable image watermarking using wavelet tree quantization

A blind and readable image watermarking scheme using wavelet tree quantization is proposed. In order to increase the algorithm robustness and ensure the watermark integrity,error correction coding techniques are used to encode the embedded watermark. In the watermark embedding process, the wavelet coefficients of the host image are grouped into wavelet trees and each watermark bit is embedded by using two trees. The trees are so quantized that they exhibit a large enough statistical difference, which will later be used for watermark extraction. The experimental results show that the proposed algorithm is effective and robust to common image processing operations and some geometric operations such as JPEG compression, JPEG2000 compression, filtering, Gaussian noise attack, and row-column removal. It is demonstrated that the proposed technique is practical.

Fast encoding algorithm for vector quantization based on subvector L_2-norm

A fast encoding algorithm based on the mean square error （MSE） distortion for vector quantization is introduced. The vector, which is effectively constructed with wavelet transform （WT） coefficients of images, can simplify the realization of the non-linear interpolated vector quantization （NLIVQ） technique and make the partial distance search （PDS） algorithm more efficient. Utilizing the relationship of vector L2-norm and its Euclidean distance, some conditions of eliminating unnecessary codewords are obtained. Further, using inequality constructed by the subvector L2-norm, more unnecessary codewords are eliminated. During the search process for code, mostly unlikely codewords can be rejected by the proposed algorithm combined with the non-linear interpolated vector quantization technique and the partial distance search technique. The experimental results show that the reduction of computation is outstanding in the encoding time and complexity against the full search method.

Image Coding Using Wavelet Transform and EntropyConstrained Vector Quantization with Quadtree Structure Vectors

This paper presents a new wavelet transform image coding method. On the basis of a hierarchical wavelet decomposition of images, entropy constrained vector quantization is employed to encode the wavelet coefficients at all the high frequency bands with

Quantization-Based Robust Image Watermarking Using the Dual Tree Complex Wavelet Transform

Conventional quantization index modulation (QIM) watermarking uses the fixed quantization step size for the host signal.This scheme is not robust against geometric distortions and may lead to poor fidelity in some areas of content.Thus,we proposed a quantization-based image watermarking in the dual tree complex wavelet domain.We took advantages of the dual tree complex wavelets (perfect reconstruction,approximate shift invariance,and directional selectivity).For the case of watermark detecting,the probability of false alarm and probability of false negative were exploited and verified by simulation.Experimental results demonstrate that the proposed method is robust against JPEG compression,additive white Gaussian noise (AWGN),and some kinds of geometric attacks such as scaling,rotation,etc.

Algorithm of Adaptive Bit Allocation Wavelet Transform Audio Coding

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An Adaptive Method of Image CompressionBased on Wavelet Analysis

Through research for image compression based on wavelet analysis in recent years, we put forward an adaptive wavelet decomposition strategy. Whether sub-images are to be decomposed or not are decided by their energy defined by certain criterion. Then we derive the adaptive wavelet decomposition tree (AWDT) and the way of adjustable compression ratio. According to the feature of AWDT, this paper also deals with the strategies which are used to handle different sub-images in the procedure of quantification and coding of the wavelet coefficients. Through experiments, not only the algorithm in the paper can adapt to various images, but also the quality of recovered image is improved though compression ratio is higher and adjustable. When their compression ratios are near, the quality of subjective vision and PSNR of the algorithm are better than those of JPEG algorithm.

Wavelet-Based Mixed-Resolution Coding Approach Incorporating with SPT for the Stereo Image

With the advances of display technology, three-dimensional(3-D) imaging systems are becoming increasingly popular. One way of stimulating 3-D perception is to use stereo pairs, a pair of images of the same scene acquired from different perspectives. Since there is an inherent redundancy between the images of a stereo pairs, data compression algorithms should be employed to represent stereo pairs efficiently. The proposed techniques generally use block-based disparity compensation. In order to get the higher compression ratio, this paper employs the wavelet-based mixed-resolution coding technique to incorporate with SPT-based disparity-compensation to compress the stereo image data. The mixed-resolution coding is a perceptually justified technique that is achieved by presenting one eye with a low-resolution image and the other with a high-resolution image. Psychophysical experiments show that the stereo image pairs with one high-resolution image and one low-resolution image provide almost the same stereo depth to that of a stereo image with two high-resolution images. By combining the mixed-resolution coding and SPT-based disparity-compensation techniques, one reference (left) high-resolution image can be compressed by a hierarchical wavelet transform followed by vector quantization and Huffman encoder. After two level wavelet decompositions, for the low-resolution right image and low-resolution left image, subspace projection technique using the fixed block size disparity compensation estimation is used. At the decoder, the low-resolution right subimage is estimated using the disparity from the low-resolution left subimage. A full-size reconstruction is obtained by upsampling a factor of 4 and reconstructing with the synthesis low pass filter. Finally, experimental results are presented, which show that our scheme achieves a PSNR gain (about 0.92dB) as compared to the current block-based disparity compensation coding techniques.

Fast 2-D 8×8 discrete cosine transform algorithm for image coding

A new fast two-dimension 8×8 discrete cosine transform （2D 8×8 DCT） algorithm based on the characteristics of the basic images of 2D DCT is presented. The new algorithm computes each DCT coefficient in turn more independently. Hence, the new algorithm is suitable for 2D DCT pruning algorithm of pruning away any number of high-frequency components of 2D DCT. The proposed pruning algorithm is more efficient than the existing pruning 2D DCT algorithms in terms of the number of arithmetic operations, especially the number of multiplications required in the computation.

Second Generation Wavelet Applied to Lossless Compression Coding of Image

In this paper, the second generation wavelet transform is applied to image lossless coding, according to its characteristic of reversible integer wavelet transform. The second generation wavelet transform can provide higher compression ratio than Huffman coding while it reconstructs image without loss compared with the first generation wavelet transform. The experimental results show that the se cond generation wavelet transform can obtain excellent performance in medical image compression coding.

Application and Analysis of Wavelet Transform in Image Edge Detection

For the image processing technology, technicians have been looking for a convenient and simple detection method for a long time, especially for the innovation research on image edge detection technology. Because there are a lot of original information at the edge during image processing, thus, we can get the real image data in terms of the data acquisition. The usage of edge is often in the case of some irregular geometric objects, and we determine the contour of the image by combining with signal transmitted data. At the present stage, there are different algorithms in image edge detection, however, different types of algorithms have divergent disadvantages so It is diffi cult to detect the image changes in a reasonable range. We try to use wavelet transformation in image edge detection, making full use of the wave with the high resolution characteristics, and combining multiple images, in order to improve the accuracy of image edge detection.

VLSI Implementation of a Wavelet Image Coder

A modular architecture for two dimension (2 D) discrete wavelet transform (DWT) is designed.The image data can be wavelet transformed in real time,and the structure can be easily scaled up to higher levels of DWT.A fast zerotree image coding (FZIC) algorithm is proposed by using a simple sequential scan order and two flag maps.The VLSI structure for FZIC is then presented.By combining 2 D DWT and FZIC,a wavelet image coder is finally designed.The coder is programmed,simulated,synthesized,and successfully verified by ALTERA CPLD.

Adaptive template filter method for image processing based on immune genetic algorithm

To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.

A Novel Color Image Watermarking Method with Adaptive Scaling Factor Using Similarity-Based Edge Region

This study aimed to deal with three challenges:robustness,imperceptibility,and capacity in the image watermarking field.To reach a high capacity,a novel similarity-based edge detection algorithm was developed that finds more edge points than traditional techniques.The colored watermark image was created by inserting a randomly generated message on the edge points detected by this algorithm.To ensure robustness and imperceptibility,watermark and cover images were combined in the high-frequency subbands using Discrete Wavelet Transform and Singular Value Decomposition.In the watermarking stage,the watermark image was weighted by the adaptive scaling factor calculated by the standard deviation of the similarity image.According to the results,the proposed edge-based color image watermarking technique has achieved high payload capacity,imperceptibility,and robustness to all attacks.In addition,the highest performance values were obtained against rotation attack,to which sufficient robustness has not been reached in the related studies.

Lossy-to-Lossless Compression of Hyperspectral Image Using the 3D Set Partitioned Embedded ZeroBlock Coding Algorithm

In this paper, we propose a three-dimensional Set Partitioned Embedded ZeroBlock Coding (3D SPEZBC) lossy-to-lossless compression algorithm for hyperspectral image which is an improved three-dimensional Embedded ZeroBlock Coding (3D EZBC) algorithm. The algorithm adopts the 3D integer wavelet packet transform proposed by Xiong et al. to decorrelate, the set-based partitioning zeroblock coding to process bitplane coding and the con-text-based adaptive arithmetic coding for further entropy coding. The theoretical analysis and experimental results demonstrate that 3D SPEZBC not only provides the same excellent compression performances as 3D EZBC, but also reduces the memory requirement compared with 3D EZBC. For achieving good coding performance, the diverse wave-let filters and unitary scaling factors are compared and evaluated, and the best choices were given. In comparison with several state-of-the-art wavelet coding algorithms, the proposed algorithm provides better compression performance and unsupervised classification accuracy.

A New Quality Improving Scheme for VQ Decompressed Images Based on DWT

The better compression rate can be achieved by the traditional vector quantization （VQ） method, and the quality of the recovered image can also be accepted. But the decompressed image quality can not be promoted efficiently, so how to balance the image compression rate and image recovering quality is an important issue, in this paper, an image is transformed by discrete wavelet transform （DWT） to generate its DWT transformed image which can be compressed by the VQ method further. Besides, we compute the values between the DWT transformed image and decompressed DWT transformed image as the difference matrix which is the adjustable basis of the decompressed image quality. By controlling the deviation of the difference matrix, there can be nearly Iossless compression for the VQ method. Experimental results show that when the number of compressed bits by our method is equal to the number of those bits compressed by the VQ method, the quality of our recovered image is better. Moreover, the proposed method has more compression capability comparing with the VQ scheme.