Ching-Min Cheng

Color image processing by using binary quaternion-moment-preserving thresholding 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.

A novel block truncation coding of color images by using quaternion-moment-preserving principle

To compress color-pixel blocks, a novel color BTC algorithm, called the quaternion-moment block truncation coding (QMBTC), is presented in this paper. The QMBTC are derived by using the quaternion arithmetic and moment-preserving principle. The proposed color BTC algorithm can adaptively truncate a pixel block into one or two output classes according to the distribution of color values inside the blocks. The experimental results show that the compression ratio will increase as compared with existing color BTC algorithms and the picture quality of reconstructed images is satisfactory.

A novel block truncation coding of color images using a quaternion-moment-preserving principle

Block truncation coding (BTC) is an efficient tool for image compression. To compress color-pixel blocks, a novel color BTC algorithm, called quaternion-moment block truncation coding (QMBTC), is presented. Analytical formulas for QMBTC, whose computation time is on the order of pixel block size, are derived by using quaternion arithmetic and the moment-preserving principle. The proposed color BTC algorithm can adaptively truncate a pixel block into one or two output classes according to the distribution of the color values inside the blocks. The experimental results show that the compression ratio is increased as compared with existing color BTC algorithms, and the picture quality of the reconstructed images is satisfactory. In addition, a post-BTC data compression scheme is proposed to further compress the subimage constructed by reproduction colors of truncated pixel blocks. Using a lookup table to display decoded data, this postprocessing scheme can output images acceptable to human eyes.

Extracting color features and dynamic matching for image database retrieval

Color-based indexing is an important tool in image database retrieval. Compared with other features of the image, color features are less sensitive to noise and background complication. Based on the human visual systems perception of color information, this paper presents a dependent scalar quantization approach to extract the characteristic colors of an image as color features. The characteristic colors are suitably arranged in order to obtain a sequence of feature vectors. Using this sequence of feature vectors, a dynamic matching method is then employed to match the query image with database images for a nonstationary identification environment. The empirical results show that the characteristic colors are reliable color features for image database retrieval. In addition, the proposed matching method has acceptable accuracy of image retrieval compared with existing methods.

Dependent scalar quantization of color images

Many image display devices can allow only a limited number of colors, called color palette, to be simultaneously displayed. In order to have a faithful color reproduction of an image, the associated color palette must be suitably designed. This paper presents a dependent scalar quantization algorithm to design the color palette effectively. The dependent scalar quantization algorithm consists of two procedures, bit allocation and recursive binary moment preserving thresholding. The experimental results show that the dependent scalar quantization can reduce the computation complexity and its output images quality is acceptable to the human eyes. A rule of the quantization order is also deduced under the MSE criterion to obtain a dependent scalar quantizer which has as good a performance as compared with some other algorithms. In addition, an adaptive neighborhood-clustering algorithm, which searches the neighboring color indices of input pixels iteratively, is proposed to further improve the performance of the dependent scalar quantization algorithm. Finally, we introduce a color mapping method to reduce the contouring effect when the color palette size generated by the dependent scalar quantizer is small. >

A fast two-class classifier for 2D data using complex-moment-preserving principle

A new moment-preserving classifier for two-class clustering is suggested. Based on preserving the complex moments of two-dimensional (2D) input data, an analytic, non-iterative and unsupervised classifier is proposed. This new classifier is suitable for applications requiring fast automatic two-class clustering of 2D data or fast automatic hierarchical clustering. Furthermore, the computation time is of order of data size and hence much faster than the well known iterative k-means algorithm. Experimental results show that the proposed classifier can acquire acceptable clustering results.

High speed video compression testbed

This paper proposes a parallel processing architecture for a video compression testbed. Experiments for video coding algorithms can be performed and evaluated under this parallel processing architecture. The features of this testbed include (1) simulations of various hardware architectures, (2) test of specialized video compression circuits, and (3) testing ASICs for embedded applications as direct replacement of algorithms that have been certified. We illustrate its implementation, performance evaluation and benchmarking via JPEG/MPEG applications. >

Limited color display for compressed video

Many display devices now allow a number of colors, called color palette, to be displayed simultaneously. Besides, images and videos in most world wide web (WWW) databases are in compressed formats. Therefore, it becomes an important issue to retrieve a suitable color palette from compressed domain in order to have fast and faithful color reproduction for these devices. In this paper, the color palette design methods for compressed videos are presented. The proposed approaches use the reduced image rather than the whole image for the color palette design to avoid the heavy computation in video decompression. Experimental results show that output image quality of proposed methods is acceptable, to human eyes. In addition, empirical results show that the proposed shifting window scheme can reduce the main problem of displaying quantized image sequences and screen flicker.