Color image processing pipeline

Digital still color cameras (DSCs) have gained significant popularity in recent years, with projected sales in the order of 44 million units by the year 2005. Such an explosive demand calls for an understanding of the processing involved and the implementation issues, bearing in mind the otherwise difficult problems these cameras solve. This article presents an overview of the image processing pipeline, first from a signal processing perspective and later from an implementation perspective, along with the tradeoffs involved.     

Color image processing using adaptive multichannel filters

New adaptive filters for color image processing are introduced and analyzed. The proposed adaptive methodology constitutes a unifying and powerful framework for multichannel signal processing. Using the proposed methodology, color image filtering problems are treated from a global viewpoint that readily yields and unifies previous, seemingly unrelated, results. The new filters utilize Bayesian techniques and nonparametric methodologies to adapt to local data in the color image. The principles behind the new filters are explained in detail. Simulation studies indicate that the new filters are computationally attractive and have excellent performance.     

基于FPGA的彩色图像增强系统

提高显示器的视觉效果,提出增强比度扩展和色饱和度两种算法,来对彩色图像进行增强处理,为满足视频信号的实时性要求,应用FPGA构造高速图像处理系统.实验结果表明,本方法能提高图像的层次感,增强色彩饱和度,达到显著提升视觉感受的效果.     

Color image processing by using binary quaternion-moment-preservingthresholding technique

This paper presents a new moment-preserving thresholding technique, called the binary quaternion-moment-preserving (BQMP) thresholding, for color image data. Based on representing color data by the quaternions, the statistical parameters of color data can be expressed through the definition of quaternion moments. Analytical formulas of the BQMP thresholding can thus be determined by using the algebra of the quaternions. The computation time for the BQMP thresholding is of order of the data size. By using the BQMP thresholding, quaternion-moment-based operators are designed for the application of color image processing, such as color image compression, multiclass clustering of color data, and subpixel color edge detection. The experimental results show that the proposed operator for color image compression can have output picture quality acceptable to human eyes. In addition, the proposed edge operator can detect the color edge at the subpixel level. Therefore, the proposed BQMP thresholding can be used as a tool for color image processing.     

Assessment of healing kinetics through true color image processing

A quantitative method of skin healing assessment using true color image processing is presented. The method was developed during a clinical trial using healthy volunteers, the goal of which was to study a drug for accelerating healing. Photographic images of the skin were sequentially acquired between day 1 and day 12 after pure painless epidermal wounds. The images were digitized in controlled conditions using a color video camera connected to a computer system. A color threshold based segmentation was developed to provide an operator-independent delineation of the wound. Two healing indexes were built measuring, the wound area and the wound color. The method was implemented in a software system allowing a fully automated determination of the healing indexes. The method provides a new quantitative global assessment of healing kinetics. It is noninvasive and well suited for multicentric clinical trials.     

Automated DNA fragments recognition and sizing through AFM image processing.

This paper presents an automated algorithm to determine DNA fragment size from atomic force microscope images and to extract the molecular profiles. The sizing of DNA fragments is a widely used procedure for investigating the physical properties of individual or protein-bound DNA molecules. Several atomic force microscope (AFM) real and computer-generated images were tested for different pixel and fragment sizes and for different background noises. The automated approach minimizes processing time with respect to manual and semi-automated DNA sizing. Moreover, the DNA molecule profile recognition can be used to perform further structural analysis. For computer-generated images, the root mean square error incurred by the automated algorithm in the length estimation is 0.6% for a 7.8 nm image pixel size and 0.34% for a 3.9 nm image pixel size. For AFM real images we obtain a distribution of lengths with a standard deviation of 2.3% of mean and a measured average length very close to the real one, with an error around 0.33%.     

Colour in image processing

Colour imaging is now commonplace in industrial and scientific applications and in domestic and professional photography. The digital processing of colour images for analysis, enhancement, or colour measurement is also common. This paper introduces the nature of colour, its electronic representation, and the concepts of luminance and chrominance. The complexities of precision image acquisition and display are outlined and the paper then discusses the fundamental processing concepts of component-wise and vector filtering and shows that there are still new developments to be expected in the digital processing of colour images     

Digital image processing

A review of the field of digital image processing is presented, with concentration upon image formation and recording processes, digital sampling and digital image display, and with in-depth coverage of image coding and image restoration. New results in image restoration are also presented, covering restoration by use of an eye-model constraint and nonlinear restoration by maximization of the posterior density function.     

From image processing to feature processing

The possibility to extract the desired features directly from Synthetic Aperture Radar (SAR) raw data without intermediate generation of the image is explored. Two implementations relative to detection of bright lines in SAR imagery are presented, and their advantages discussed.     

Transition detection in image processing

Image data can be modelled by stationary autoregressive (AR) models. However, local nonstationarities called events result in irregular properties. Detection of events using local statistical properties of residual sequences, jumps in model parameters, Laplacian output of data, and steepness measure of data have been discussed and a detection procedure has been suggested.     

Color image resolution conversion.

In this paper, we look at the problem of spatially scaling color images. We focus on an approach that takes advantage of the human visual system's color spatial frequency sensitivity. The algorithm performs an efficient least-squares (LS) resolution conversion for the luminance channel and a low-complexity pixel replication/reduction in the chrominance channels. The performance of the algorithm is compared to a LS method in sRGB and CIELAB color spaces, as well as standard bilinear interpolation in sRGB space. The comparisons are made in terms of computational cost and color error in sCIELAB.     

Color image fidelity metrics evaluated using image distortion maps

Several color image fidelity metrics are evaluated by comparing the metric predictions to empirical measurements. Subjects examined image pairs consisting of an original and a reproduction. They marked locations on the reproduction that differed detectably from the original. We refer to the distribution of error marks by the subjects as image distortion maps. The empirically obtained image distortion maps are compared to the predicited visible difference calculated using (1) the widely used root mean square error (point-by-point RMS) computed in uncalibrated RGB values, (2) the point-by-point CIELAB ΔE₉₄ values (CIE, 1994), and (3) S-CIELAB ΔE₉₄, a spatial extension of CIELAB ΔE metric. The uncalibrated RMS metric did not predict the perceptual image distortion data well. The point-by-point CIELAB ΔE₉₄ metric provided better predictions, and the S-CIELAB metric, which incorporated the spatial color sensitivity of the eye, gave the most accurate predictions. None of the metrics provided an excellent fit to the data. Image areas with poor predictions were concentrated in regions containing large negative local contrast. When these areas were excluded from our data analysis, both S-CIELAB and CIELAB predictions had much better agreement with the perceptual data. This suggests that the next step in improving color image fidelity metrics is to redefine color difference formula such as CIELAB ΔE₉₄ in terms of local contrast.     

Bayesian image processing in two dimensions

A Bayesian image processing (BIP) formalism which incorporates a priori amplitude and spatial probability density information was applied to two-dimensional source fields. For valid, moderately restrictive a priori information, strikingly improved results for ideal and experimental radioisotope phantom imaging data, compared to a standard non-Bayesian formalism (maximum likelihood, ML), were obtained. The applicability of a fast Fourier transform technique for "convolution" calculations, a reduced-region restriction for the initial "deconvolution" calculations, and a relaxation parameter for accelerating convergence are considered.     

Order statistics in digital image processing

A family of nonlinear filters based on order statistics is presented. A mathematical tool derived through robust estimation theory, order statistics has allowed engineers to develop nonlinear filters with excellent robustness properties. These filters are well suited to digital image processing because they preserve the edges and the fine details of an image much better than conventional linear filters. The probabilistic and deterministic properties of the best known and most widely used filter in this family, the median filter, are discussed. In addition, the authors consider filters that, while not based on order statistics, are related to them through robust estimation theory. A table that ranks nonlinear filters under a variety of performance criteria is included. Most of the topics treated are very active research areas, and the applications are varied, including HDTV, multichannel signal processing of geophysical and ECG/EEG data, and a variety of telecommunications applications