基于HSV颜色空间的改进的多尺度Retinex算法

针对带颜色恢复的多尺度Retinex算法在最后输出的图像上存有重叠的问题,提出了一种改进的子频带分解的Retinex算法,该算法不仅能增强亮点中的细节,也能增强在阴影中的细节.由于RGB这三种颜色之间有很强的关系,而HSV这三者之间没有很大的关联,能够较好的反映人对色彩的感知.实验结果表明,与基于RGB空间的多尺度Retinex算法相比,改进的基于HSV的算法更有效的增强图像在亮点和阴影中的细节,颜色更接近于原图.     

Noise reduction using multiscale bilateral decomposition for digital color images

In this paper, we propose a noise reduction algorithm for digital color images using a nonlinear image decomposition approach. Most existing noise reduction methods do not adequately consider spatial correlation of color noise in digital color images. Color noise components in color images captured by digital cameras are observed as irregular grains with various sizes and shapes, which are spatially randomly distributed. We use a modified multiscale bilateral decomposition to effectively separate signal and mixed-type noise components, in which a noisy input image is decomposed into a base layer and several detail layers. A base layer contains strong edges, and most of noise components are contained in detail layers. Noise components in detail layers are reduced by an adaptive thresholding function. We obtain a denoised image by combining a base layer and noise-reduced detail layers. Experimental results show the effectiveness of the proposed algorithm, in terms of both the peak signal-to-noise ratio and visual quality.     

Personal communications networks bridging the gap between cellularand cordless phones

Today's cellular radiotelephone systems currently serve some 12 million subscribers but at average costs of $70/month for service, cellular remains a business, not a consumer, service. On the other hand, cordless phones are already a consumer product in over 40% of US households and annual sales of new cordless phones are already greater than sales of regular corded phones. Personal Communications Networks (PCN) providing Personal Communications Services (PCS) are designed to bridge the gap between expensive public cellular and private cordless services. In this paper we explore PCN/PCS topics including: a definition of the service, identification of the underlying technologies, and discussion of tradeoffs between the technologies     

A non-parametric depth modification model for registration between color and depth images

Multidimensional Systems and Signal Processing - Despite its most popularity among all depth cameras in the computer vision applications, the Microsoft Kinect sensor suffers from low depth...     

A hierarchical Markovian model for multiscale region-based classification of vector-valued images

We propose a new classification method for vector-valued images, based on: 1) a causal Markovian model, defined on the hierarchy of a multiscale region adjacency tree (MRAT), and 2) a set of nonparametric dissimilarity measures that express the data likelihoods. The image classification is treated as a hierarchical labeling of the MRAT, using a finite set of interpretation labels (e.g., land cover classes). This is accomplished via a noniterative estimation of the modes of posterior marginals (MPM), inspired from existing approaches for Bayesian inference on the quadtree. The paper describes the main principles of our method and illustrates classification results on a set of artificial and remote sensing images, together with qualitative and quantitative comparisons with a variety of pixel-based techniques that follow the Bayesian-Markovian framework either on hierarchical structures or the original image lattice.     

A high-quality fixed-length compression scheme for color images

We present a new compression method which compresses 8×8 picture blocks by fixed-length codewords. The compression operation is performed on the discrete cosine transforms, DCT, of each block. As a result, our method combines the distinct advantage of being fixed-length with the high image quality obtained by the DCT based compression methods. Our method has excellent error-resistance characteristics since it does not have the synchronization and error propagation problems inherent in variable-length coding methods     

一种鲁棒的彩色图像多功能水印算法

首先转换彩色图像的颜色空间抽取相应的灰度图像,再对灰度图像进行提升小波分解,在分解过程中利用图像压缩操作,引起近半数的小波系数增大,另一半系数减小,基于系数增减特征实现版权水印和消费者数字指纹的同时嵌入,从而获得版权认证和盗版追踪的双重功能。仿真实验表明该算法具有良好的鲁棒性和不可感知性。     

A novel approach for coding color quantized images

An approach to the lossy compression of color images with limited palette that does not require color quantization of the decoded image is presented. The algorithm is particularly suited for coding images using an image-dependent palette. The technique restricts the pixels of the decoded image to take values only in the original palette. Thus, the decoded image can be readily displayed without having to be quantized. For comparable quality and bit rates, the technique significantly reduces the decoder computational complexity.     

A multiscale dynamic programming procedure for boundary detection in ultrasonic artery images

Ultrasonic measurements of human carotid and femoral artery walls are conventionally obtained by manually tracing interfaces between tissue layers. The drawbacks of this method are the interobserver variability and inefficiency. In this paper, we present a new automated method which reduces these problems. By applying a multiscale dynamic programming (DP) algorithm, approximate vessel wall positions are first estimated in a coarse-scale image, which then guide the detection of the boundaries in a fine-scale image. In both cases, DP is used for finding a global optimum for a cost function. The cost function is a weighted sum of terms, in fuzzy expression forms, representing image features and geometrical characteristics of the vessel interfaces. The weights are adjusted by a training procedure using human expert tracings. Operator interventions, if needed, also take effect under the framework of global optimality. This reduces the amount of human intervention and, hence, variability due to subjectiveness. By incorporating human knowledge and experience, the algorithm becomes more robust. A thorough evaluation of the method in the clinical environment shows that interobserver variability is evidently decreased and so is the overall analysis time. We conclude that the automated procedure can replace the manual procedure and leads to an improved performance.     

A new multiscale Bayesian algorithm for speckle reduction in medical ultrasound images

This paper introduces a new multiscale speckle reduction method based on the extraction of wavelet interscale dependencies to visually enhance the medical ultrasound images and improve clinical diagnosis. The logarithm of the image is first transformed to the oriented dual-tree complex wavelet domain. It is then shown that the adjacent subband coefficients of the log-transformed ultrasound image can be successfully modeled using the general form of bivariate isotropic stable distributions, while the speckle coefficients can be approximated using a zero-mean bivariate Gaussian model. Using these statistical models, we design a new discrete bivariate Bayesian estimator based on minimizing the mean square error (MSE). To assess the performance of the proposed method, four image quality metrics, namely signal-to-noise ratio, MSE, coefficient of correlation, and edge preservation index, were computed on 80 medical ultrasound images. Moreover, a visual evaluation was carried out by two medical experts. The numerical results indicated that the new method outperforms the standard spatial despeckling filters, homomorphic Wiener filter, and new multiscale speckle reduction methods based on generalized Gaussian and symmetric alpha-stable priors.     

A fuzzy noise reduction method for color images.

A new fuzzy filter is presented for the reduction of additive noise for digital color images. The filter consists of two subfilters. The first subfilter computes fuzzy distances between the color components of the central pixel and its neighborhood. These distances determine in what degree each component should be corrected. All performed corrections preserve the color component distances. The goal of the second subfilter is to correct the pixels where the color components differences are corrupted so much that they appear as outliers in comparison to their environment. Experimental results show the feasibility of the proposed approach. We compare with other noise reduction methods by numerical measures and visual observations. We also illustrate the performance of the proposed method as preprocessing step for edge detection.     

A color map for effective black-and-white rendering of color-scale images

Default color maps on color images often reproduce to confusing grayscale images. The proposed color map maintains an aesthetically pleasing color image that automatically reproduces to a monotonic grayscale with discrete, quantifiable saturation levels.     

Advantages of multiscale product filters for dynamic range compression in images

A multiscale product filter (MSPF) structure is proposed for use in digital image enhancement. The objective for this type of image processing is to mitigate the effect of uneven illumination on perceived image quality, a process known as dynamic range compression (DRC). The properties of the MSPF for DRC are investigated, a theoretical model is presented, and this model is used to predict the performance of the filter under step changes in illumination such as those caused by shadows. The advantage of the MSPF is that it provides a relatively rapid response for transitions from shadow regions to well-lit regions. This property is verified using random Mondrian textures with simulated illumination changes. The estimated illumination profile is compared with that used to generate the synthetic image using the Pearson's correlation coefficient. The improved performance of the MSPF is also confirmed by the mitigation of shadow artefacts in real images     

Directional multiscale modeling of images using the contourlet transform.

The contourlet transform is a new two-dimensional extension of the wavelet transform using multiscale and directional filter banks. The contourlet expansion is composed of basis images oriented at various directions in multiple scales, with flexible aspect ratios. Given this rich set of basis images, the contourlet transform effectively captures smooth contours that are the dominant feature in natural images. We begin with a detailed study on the statistics of the contourlet coefficients of natural images: using histograms to estimate the marginal and joint distributions and mutual information to measure the dependencies between coefficients. This study reveals the highly non-Gaussian marginal statistics and strong interlocation, interscale, and interdirection dependencies of contourlet coefficients. We also find that conditioned on the magnitudes of their generalized neighborhood coefficients, contourlet coefficients can be approximately modeled as Gaussian random variables. Based on these findings, we model contourlet coefficients using a hidden Markov tree (HMT) model with Gaussian mixtures that can capture all interscale, interdirection, and interlocation dependencies. We present experimental results using this model in image denoising and texture retrieval applications. In denoising, the contourlet HMT outperforms other wavelet methods in terms of visual quality, especially around edges. In texture retrieval, it shows improvements in performance for various oriented textures.     

A lossless compression scheme for Bayer color filter array images.

In most digital cameras, Bayer color filter array (CFA) images are captured and demosaicing is generally carried out before compression. Recently, it was found that compression-first schemes outperform the conventional demosaicing-first schemes in terms of output image quality. An efficient prediction-based lossless compression scheme for Bayer CFA images is proposed in this paper. It exploits a context matching technique to rank the neighboring pixels when predicting a pixel, an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples, and an adaptive codeword generation technique to adjust the divisor of Rice code for encoding the prediction residues. Simulation results show that the proposed compression scheme can achieve a better compression performance than conventional lossless CFA image coding schemes.     

基于子带金字塔结构的彩色图像小波编码

本文改进了分层树集分割算法(SPIHT),重新设计了一种子带金字塔的数据结构来组织图像的二维小波变换系数,既减少了存储空间又加快了编码速度.在彩色图像的YUV空间按位平面的顺序依次对YUV三个分量编码,输出颜色分量完全嵌入式的码流.实验结果表明改进后算法对彩色图像的编码能获得很好的率失真性能,而且适用于高分辨率、不规则图像的编解码.     

基于FPGA与DSP的实时视频图像偏色校正系统

提出一种基于FPGA与DSP的实时视频图像偏色校正系统,包括数字视频解码芯片、FPGA、DSP以及数字视频编码芯片。该系统能以一种格式接收视频图像信号并以相同的格式输出,输出偏色校正后的视频信号相比输入的视频信号而言,延迟非常小,实时性强,是一种较为实用的视频图像偏色校正系统。     

On independent color space transformations for the compression ofCMYK images

Device and image-independent color space transformations for the compression of CMYK images were studied. A new transformation (to a YYCC color space) was developed and compared to known ones. Several tests were conducted leading to interesting conclusions. Among them, color transformations are not always advantageous over independent compression of CMYK color planes. Another interesting conclusion is that chrominance subsampling is rarely advantageous in this context. Also, it is shown that transformation to YYCC consistently outperforms the transformation to YCbCrK, while being competitive with the image-dependent KLT-based approach.     

A contribution of image processing to the diagnosis of diabetic retinopathy--detection of exudates in color fundus images of the human retina

In the framework of computer assisted diagnosis of diabetic retinopathy, a new algorithm for detection of exudates is presented and discussed. The presence of exudates within the macular region is a main hallmark of diabetic macular edema and allows its detection with a high sensitivity. Hence, detection of exudates is an important diagnostic task, in which computer assistance may play a major role. Exudates are found using their high grey level variation, and their contours are determined by means of morphological reconstruction techniques. The detection of the optic disc is indispensable for this approach. We detect the optic disc by means of morphological filtering techniques and the watershed transformation. The algorithm has been tested on a small image data base and compared with the performance of a human grader. As a result, we obtain a mean sensitivity of 92.8% and a mean predictive value of 92.4%. Robustness with respect to changes of the parameters of the algorithm has been evaluated.