This paper proposes a new stereo sequence transmission technique using digital watermarking for compatibility with conventional 2D digital TV. We, generally, compress and transmit image sequence using temporal-spatial redundancy between stereo images. It is difficult for users with conventional digital TV to watch the transmitted 3D image sequence because many 3D image compression methods are different. To solve such a problem, in this paper, we perceive the concealment of new information of digital watermarking and conceal information of the other stereo image into three channels of the reference image. The main target of the technique presented is to let the people who have conventional DTV watch stereo movies at the same time. This goal is reached by considering the response of human eyes to color information and by using digital watermarking. To hide right images into left images effectively, bit-change in 3 color channels and disparity estimation according to the value of estimated disparity are performed. The proposed method assigns the displacement information of right image to each channel of YCbCr on DCT domain. Each LSB bit on YCbCr channels is changed according to the bits of disparity information. The performance of the presented methods is confirmed by several computer experiments.
The current paper proposes a fast stereo matching algorithm based on a pixel-wise matching strategy that can produce a stable and accurate disparity map. Since the differences between a pair of stereo images are only small and such differences are just caused by horizontal shifts in a certain order, matching using a large window is not required within a given search range. Therefore, the current study adopts a disparity space image(DSI) for efficient pixel-wise matching. In a DSI, each disparity value is derived from the matching path. As such, when the matching path in a DSI innately satisfies the ordering constraint, continuous matching is possible. In addition, since this continuous matching also considers neighbor pixels, it assumes the characteristics of region-based matching, similar to window-based matching, yet with a lower computational load. To avoid the unstable characteristic of the pixel-based matching, we modified the directions in the cost array in the dynamic programming(DP). Experimental results demonstrate that the proposed method can remove almost all disparity noise and produce a good quality disparity map within a very short time.
The current paper proposes an efficient method for edge detection in original and noisy images using Waerden's statistic. Edges represent a significant amount of information on an image. For example, edges reveal the location of objects, their shape and size, and something about their texture. Since edges represent where the intensity of an image moves from a low value to a high value or vice versa, edge detection is often the first step in image segmentation. As a field of image analysis, image segmentation groups pixels into regions to determine the image composition. Therefore, the current paper describes the nonparametric Wilcoxon test and parametric T test based on statistical hypothesis testing for edge detection. Here, the threshold is determined by specifying a significance level, whereas Bovik, Huang, and Munson considered a range of possible test statistic values for the threshold. In the current study, the test statistic is calculated based on pixel gray levels obtained using an edge-height parameter and compared with the threshold determined by a significance level. Experiments were conducted to evaluate the performance of these methods in both original and noisy images. As a result, the Wilcoxon and T test was found to be sensitive to a noisy image, whereas the proposed Waerden test was robust in both noisy and noise-free images under α=0.0005. Furthermore, when compared with Sobel, LoG, and Canny operators, the proposed Waerden test was also more effective in both noisy and noise-free images.
This paper proposes a gamut mapping algorithm based on color space division for color reproduction of cross media. As each color device has a limited range of producible colors, the reproduced colors on a destination device are different from those of the original device. In order to reduce the color difference between those devices, the proposed method divides the whole gamut into parabolic shapes based on intersecting lightness by the “just noticeable difference” (JND) and the boundary of original gamut. By dividing the gamut with parabolic shapes and piecewise mapping of each region, it not only considers gamut characteristics but also provides for mapping uniformity. The lightness variations are more sensitive to the human visual system and by using lightness JND it can restrict lightness mapping variations that are unperceivable. As a result, the proposed algorithm is able to reproduce high quality color images using low-cost color devices.
In this paper, we propose an adaptive stereo matching algorithm to treat stereo matching problems in projective distortion regions. Since the disparities in the projective distortion region can not be estimated in terms of fixed- size block matching algorithm, an adaptive window warping method with hierarchical matching process is used to compensate perspective distortions. In addition, a probability model, based on the statistical distribution of matched errors and constraint functions, is adopted to handle the uncertainty of matching points. Since the proposed window warping process is based on a statistical window warping step with the reliability estimation of matching points, any relaxation process need not to use. As a result, overall processing time is reduced, compared with conventional stereo matching algorithm including a relaxation step, and improved matching results are obtained. Experimental results on both disparity map and 3D model view show that the proposed matching algorithm is effective for various images, even if the image has projective distortion regions and repeated patterns.
In this paper, we proposed the digital watermarking for a color image. In order to embed watermark signal, we consider the characteristics of HVS (human visual system) and focus on the relatively insensitive components of a color image. In YCrCb color space, Y component is achromatic--luminance and both Cr and Cb components are chromatic--color. At the Cr-Cb chrominance plane, an angle of a pixel represents the hue component of a color that refers to its average spectral wavelength and differentiates different colors and a magnitude of a pixel determines the amount of purity of the color. Because the variation of saturation is less sensitive than that of hue, we modify the saturation value--the magnitude in Cr-Cb chrominance plane. On changing the chrominance data, the phase of a point has to be fixed and only the magnitude of the point that represents the saturation is changed based on the acceptable degree of color difference. The proposed digital watermarking method has a good property in the field of invisibility.
Color histogram is widely used in image retrieval due to its simplicity and fast operation sped. Since color histogram describes only global color distribution in an image, it is not robust to large changes in appearance and shape caused by viewing position, camera zoom, etc. To overcome this problem, we propose the method using the color edge information. Although changes in appearance and shape happen, the pair of colors on the color edge does not change. So we use the global distribution of pairs of colors on the color edge pixel to cope with large appearance change. In the proposed method, color edge detection based on vector angle is performed to classify the pixels of image into smooth and edge pixels. For edge pixel, the global distribution of pairs of colors around the edge is represented by 36 non-uniform colors. In the smooth compressed by DCT. Joint histogram of compressed the 2D chromaticity histogram and the global distribution of pairs of colors is very robust to large appearance changes.
This paper presents an effective object segmentation method for object-oriented coding. The process is composed of facial region detection using skin color and changed region detection using motion information. The image is then segmented between moving objects and background using motion estimation. The facial regions are detected using skin color, the data for which is obtained from the u, v image. This data is then used as a threshold to segment the facial region. The image is also segmented into changed regions using motion information. After combining these results, the final image is segmented between moving objects and background. This method is more efficient due to two factors, color and motion. Experimental results show that the proposed method can significantly improve the image quality.
This paper proposes a new 3D modeling technique based on feature points using spatio-temporal relationship. Normally, the generation of a 3D model from a real scene requires the computation of the depth of the model vertices from a dense correspondence map of the whole image. This is very time consuming, plus it is also quite difficult to achieve an accurate depth. The proposed method can generate a 3D model of an object based on identifying the correspondence of certain feature points without the need for a dense correspondence map. The proposed method consists of three parts: the extraction of an object, the extraction of feature points, and hierarchical 3D modeling using the classified feature points. This method is effective in generating a 3D model and expressing the smoothness of plain regions and sharpness of edges.