A Context Model of Wavelet Coefficients for Image Compression

Through the combination of the idea of the linear prediction used in the GlicBawls coding scheme and the idea of the quantization taken in the CALIC coding scheme to reduce the number of contexts, a new context model of wavelet coefficients for image compression is proposed. Wavelet coefficients are encoded by the arithmetic encoder, with the contexts formed by quantizing linear prediction values. Experimental results show that the model achieves higher lossless compression rate of image than lossless SPIHT and lossless EBCOT used in JPEG2000. In addition, by exploiting the multiresolution property of wavelet, the model can compress the transformed image for progressive resolution and earn higher compression rate for each scale of the image than EBCOT.     

A Medical Image Quantization Method Suited for PACS

Image compression is very important in picture archiving and communication system(PACS). The author studied the statistical distribution of image wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is similar to that of Laplasian distribution. On the other hand, in image reconstruction, the coefficient with different amplitude owns different weight, and different accuracy can be applied to different coefficients according to their different weight. Then, the author has designed a image quantization encoding scheme for PACS. In this scheme, they selected the sample-standard-deviation of coefficients in every subimage as the quantization threshold, and accurately encoded those coefficients with higher weight. Also, this algorithm utilized the visual character of human. The test has proved that the main advantages of this method are the simplicity in computing and predictable encoded coefficients, and a high compression efficiency can obtain too.     

Video Compression of Vector Coding based on Wavelet Transform

It is possible to get high compression rate for the interrelationship between neighboring frames of moving pictures. The kernel of research on video compression is that the efficient image compression algorithm is adopted while the interrelationship between neighboring frames and time consumption is concerned to improve the compression efficiency. It is significant that motion compensation is applied to video compression, nevertheless it is too time consuming. A vector coding method based on wavelet transform is presented to avoid searching procedure of motion compensation. Simulation shows that high compression rate is achieved with less time consumption.     

随机区间置换的安全算术编码及应用

基于压缩编码的加密方式能够同时完成加密和压缩的功能,通过压缩减少了信息的冗余,同时引入加密使对试图推测出明文信息和找到密钥的攻击具有非常好的鲁棒性。提出了一种基于随机区间置换的安全算术编码,在编码过程中通过随机密钥保证图像压缩编码的安全性,且不影响编码的效率,使其方便在网络中安全传输。实验结果和安全性分析表明该安全算术编码有较好的安全性和加密效率。     

Logistic map controlled secure arithmetic coding and its application in image encryption

A logistic map controlled secure arithmetic coding is proposed, the Logistic map is used to control the order of the symbols in the model and change the probabilities of the symbols, which is applied to the image encryption. The proposed scheme makes the image transmit more secure and comfortably on the Internet, and that is done at little expense in terms of coding efficiency. In the coding process, it ensures the uniformity of the model being changed by the chaotic sequence, thus to meet the security requirements of image compression. The algorithm can be applied to any arithmetic codec based on multimedia data including video, image and audio. Its most strength compared with other cipher mode is that, there is a significant reduction in the redundancy of information during the compression process, and it is robust when attempting to estimate the information of the image and discovering the key. The scheme can effectively resist differential analyses from both cryptography and coding.     

A New Solution to Reduce Blocking Artifacts Introduced by Standard Fractal Methods

Fractal image coding techniques usually partition the input image into small range blocks. This artificially introduces boundaries into the image resulting in the unpleasant blocking artifacts in the decoded images especially at high compression rate. Because the effect is especially responsible for the restrictions of the block-based coders, the solutions must be sought to reduce this blockiness. Recently two possible schemes have been proposed by other researchers: One may try to use overlapping blocks in the fractal transform, and the other to employ the combined fractal wavelet approach. An alternative solution is proposed, which employs the bilinear interpolation techniques and the resolution independence of fractal coding, in the sense that an image can be decoded at higher or lower resolutions than the original. Experiments show that the proposed scheme can eliminate the blocking artifacts.     

An algorithm of image processing based on discrete wavelet transform compression and chaotic scrambling

An algorithm was proposed in view of the combination of image compression and encryption. We got the approximate part and three detail parts after transforming the image with discrete wavelet transform (DWT), and compressed the image by modifying the detail parts by a given threshold value based on human visual systems. And then, we encrypted the image by scrambling the approximate part because this part held mostly of the energy. Last, a compressed and encrypted image can be achieved after DWT. Simulation result shows a good effect on the combination of compression and encryption.     

Multifocus image fusion scheme based on feature contrast in lifting stationary wavelet domain

A novel multifocus image fusion method based on lifting stationary wavelet transform (LSWT) is proposed. The selection principles, namely fusion rules of different subband coefficients, are discussed in detail. Local feature contrast is presented according to the human vision system (HVS), which is highly sensitive to the local image contrast level. Then, the fusion rule for the low-frequency subband coefficients fusion is introduced. To choose the high frequency subband coefficients, another local feature contrast is developed according to the human vision which is often sensitive to edges and directional features, but insensitive to real luminance at independent positions. Then, a novel fusion rule is proposed for fusion of the high frequency subband coefficients. Experimental results demonstrate that the proposed image fusion method is effective and can provide better performance in fusing multifocus images than the traditional contrast-based image fusion algorithms in term of informal visual inspection and objective criteria in multi-focus image fusion.     

Embedded Image Coding on Wavelet Coefficients

The modeling of wavelet coefficient for still image compression is studied.Firstly,through simulation experiments on three classical wavelet coefficient models(i.e.,EZW model,SPIHT model/and EBCOT model),it is shown that SPIHT is superior to EZW in terms of compression performance(0.6 dB higher)and the compression performance of EBCOT is significantly better than that of SPIHT on average. Then the cause for such performance differences is explained through the analysis of models.Finally a new wavelet coefficients model is proposed which combines the advantages of the three classical models.Experimental results show that our model is better than the above mentioned three models with respect to compression ratio.     

Adaptive Binary Arithmetic Coding on DSP

As a kind of data compression technique of high efficiency, arithmetic coding is widely used in image compressing. This paper introduces the adaptive binary arithmetic coding used in the new international standard of still image compression named jpeg2000. The implementation of arithmetic coding depends on high power digital signal processor.Fast adaptive binary arithmetic coding and optimized assembly program design are discussed, and its practicability and efficiency are proved.It also can be used in other fields that need compressing data.     

Fusion method for infrared and visible light images based on image segmentation and stationary wavelet transform

A novel image fusion method based on image segmentation and stationary wavelet transform (SWT) is proposed to improve the visual effect of fused infrared and visible light images. Infrared image is firstly separated into object and background region utilizing Otsu combined with edge detection. Then a multiresolution decomposition using SWT is made to the background region of the infrared image and the visible light image. Neighborhood spatial frequency and absolute value are adopted as fusion rules in low-frequency and high-frequency coefficients. The background fused image is reconstructed by inverse SWT. The final infrared and visible light fused image is obtained by fusing the background fused image and the object region of infrared image base on weighted fusion rule. The experimental results show that the object information of the infrared image is obviously highlighted and the scene information of the visible light image is well represented. The visual effect of fused image is improved efficiently by utilizing the proposed method. The proposed method works better than the traditional Laplacian Pyramid and wavelet transform fusion algorithms in terms of standard deviation, comentropy and mutual information. Experimental results verify its effectiveness.     

Segmentation algorithm for urinary sediment image combiningwavelet transform and 2D Maximum entropy threshold

In order to solve the problem that urine sediment visible components cannot be segmented effectively because of complex components, complicated defocusing in image and poor discrimination between object and background, a method based on combination algorithm wis designed to segment urine sediment. The wavelet transform wis used to erase the effect of defocusing. Then morphology wis utilized to get the subimages that include the particles. The segmentation method combining the wavelet transform based segmentation and the two dimensional entropy threshold based segmentation wis employed to segment urine sediment visible components. Experimental results show that the proposed method can segment urinary sediment images effectively and precisely.     

Context Model Based on 3D Wavelet Coefficients

Based on by typical coding schemes such as EZW,SPIHT, EBCOT,3D-IEZW,3D-SPIHT and 3D-ESCOT,a context model(3D-OWNER) of wavelet coefficients is proposed,which makes use of partial order,self-similarity between subbands of wavelet coefficients and the correlation of neighboring wavelet coefficients.Experimental results show that the model can achieve higher PSNR than 3D-ESCOT.     

林业专题图数字水印版权保护研究

针对林业专题图制作过程复杂、成本高、迫切需要进行版权保护的问题,分析了JPEG图像压缩的不变属性,在此基础上提出了一种DCT域数字水印算法,该算法将水印信息嵌入到JPEG格式的林业专题图像的中高频系数当中。结果表明：因为水印信息是嵌入在中高频系数上,所以不仅嵌入的水印信息不可感知性良好,而且水印的嵌入容量也有所增加;即使对加密林业专题图进行有损压缩时使用高于预设值的质量因子,此算法仍然能够完全一致地提取出嵌入的水印信息,并且对各种噪声干扰都具有较好的鲁棒性。     

Multi scale and multi orientation features for image de noising

An adaptive algorithm for image de noising is proposed based on the multi scale and multi orientation features. The coefficients in different scales and different directions are obtained by image decomposition using the nonsubsampled contourlet transform. Then thresholds functions are adaptively set with these coefficients. The texture of the image information is introduced by using the mean of decomposition scale and the energy of regional. The greater the energy, the more information of the texture while the same decomposition scales, the smaller the threshold is set. On the contrary, the greater the threshold is set. After the de noising and then reconstruction of these coefficients, image de noising is implemented. Compare to the wavelet transform threshold and contourlet transform threshold, the nonsubsampled contourlet transform pick up the image detail better and improve the quality of the image.     

Framework of M-channel Systems and the Best Symmetric Extension

In image compression based on wavelet transform, the borders of images have to be processed in advance so as to reduce the distortions around the borders. An efficient way for this problem is symmetric extension. There are different types of symmetric extension methods. The paper presents the best symmetric extension and gives a design algorithm. Using the algorithm, we obtain the scheme of extending and windowing the signals in general best M-channel analysis/synthesis system.     

Some Perspective Applied Areas of Wavelet Analysis

Some perspective applied areas of wavelet analysis are analyzed in this paper.The application of wavelet in active image compression is deeply explored and the development of wavelet is predicted.     

Audio blind watermarking scheme combined DWT DCT QR

In order to protect the copyright of digital audio and video in Internet, we propose a novel audio blind watermarking scheme combined discrete wavelets transform, discrete cosine transform, QR decomposition and audio characteristics. In this algorithm, the audio are split into blocks, and each block are decomposed on two dimensional discrete wavelet transform (DWT), then the approximate sub band coefficients are decomposed on discrete cosine transform (DCT), and the first quarter of the DCT coefficients are decomposed on QR decomposition and get a triangle matrix. At last, the watermarking information is embedded into the triangle matrix. The experiments show that the algorithm can get better balance between transparency and robustness of watermark, and it has strong robustness against the common audio signal processing such as additive white Gaussian noise, re sampling, re quantization, low pass filter, MP3 compression and cutting replacement.     

A Research on the Characteristics of Mexican-hat Mother Wavelet Used in Optic Realization

The Mexican hat mother wavelet used in optic realization is analysed. Its characteristics on time frequency domain localization, accurate reconstruction condition, regularity order and orthonormality are discussed. The error concept for the Mexican hat wavelet that the non tensor product two dimensional form of mother wavelet is obtained from the turning of its one dimensional form is corrected. The reason is explained for that the Mexican hat mother wavelet can't be used in conventional discrete wavelet transform for image data compression,but when it is used in 2 D image wavelet transform realized by optic way, it features excellent energy localization.     

Color Image Compression Method Based on Incomplete Scanning Method

In view of color image characteristic, the paper improves the zero algorithm in the application of concrete algorithm, draws a new algorithm-incomplete scanning method, which is applied to color image compression. The authorsconvert color image from the RGB space into luminance-chrominance YUV space, then compress the converted image to encode/decode. Theoretical analysis and simulation experiment indicate that the compression ratio and encoding/decoding speed are increased, at the sase time the quality of restored image is guaranteed.