Efficient methods for the calculation of radial influence are described and applied to two image processing problems, digital halftoning and mixed content image compression. The methods operate recursively on scanlines of image values, spreading intensity from scanline to scanline in proportions approximating a Cauchy distribution. For error diffusion halftoning, experiments show that this recursive scanline spreading provides an ideal pattern of distribution of error. Error diffusion using masks generated to provide this distribution of error alleviate error diffusion "worm" artifacts. The recursive scanline by scanline application of a spreading filter and a complementary filter can be used to reconstruct an image from its horizontal and vertical pixel difference values. When combined with the use of a downsampled image the reconstruction is robust to incomplete and quantized pixel difference data. Such gradient field integration methods are described in detail proceeding from representation of images by gradient values along contours through to a variety of efficient algorithms. Comparisons show that this form of gradient field integration by convolution provides reduced distortion compared to other high speed gradient integration methods. The reduced distortion can be attributed to success in approximating a radial pattern of influence. An approach to edge-based image compression is proposed using integration of gradient data along edge contours and regularly sampled low resolution image data. This edge-based image compression model is similar to previous sketch based image coding methods but allows a simple and efficient calculation of an edge-based approximation image. A low complexity implementation of this approach to compression is described. The implementation extracts and represents gradient data along edge contours as pixel differences and calculates an approximate image by performing integration of pixel difference data by scanline convolution. The implementation was developed as a prototype for compression of mixed content image data in printing systems. Compression results are reported and strengths and weaknesses of the implementation are identified.

Thesis (Ph. D.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains xii, 146 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 134-146).

Multi-view three-dimensional television requires many views, which may be synthesized from two-dimensional images with accompanying pixel-wise depth information. This depth image, which typically consists of smooth areas and sharp transitions at object borders, must be consistent with the acquired scene in order for synthesized views to be of good quality. We have previously proposed a depth image coding scheme that preserves significant edges and encodes smooth areas between these. An objective evaluation considering the structural similarity (SSIM) index for synthesized views demonstrated an advantage to the proposed scheme over the High Efficiency Video Coding (HEVC) intra mode in certain cases. However, there were some discrepancies between the outcomes from the objective evaluation and from our visual inspection, which motivated this study of subjective tests. The test was conducted according to ITU-R BT.500-13 recommendation with Stimulus-comparison methods. The results from the subjective test showed that the proposed scheme performs slightly better than HEVC with statistical significance at majority of the tested bit rates for the given contents.

There has been a great progress in the field of graphics processors. Since, there is no rise in the speed of the normal CPU processors; Designers are coming up with multi-core, parallel processors. Because of their popularity in parallel processing, GPUs are becoming more and more attractive for many applications. With the increasing demand in utilizing GPUs, there is a great need to develop operating systems that handle the GPU to full capacity. GPUs offer a very efficient environment for many image processing applications. This thesis explores the processing power of GPUs for digital image compression using Discrete cosine transform.

Fractal image compression is based on the representation of an image by contractive transforms whose xed points are close to the original image. In the encoding of fractal image compression, most of the time is spent on nding the close match between a range block and a large pool of domain blocks. In this thesis, we use the intra-block variances distributions of domain blocks to reduce the searching space. For nding a close match we need only search the domain blocks whose maximal intra-block variance quadrants are the same as that of the range block in nding a close match. The experiment results show that our algorithm can reduce much encoding time with only slight loss of quality.

Thesis (M.S.)--Naval Postgraduate School, 2002. / Thesis advisor(s): Murali Tummala, Robert Ives. Includes bibliographical references (p. 95-97). Also available online.

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xxv, 142 p.; also includes graphics. Includes abstract and vita. Advisor: Yuan F. Zheng, Dept. of Electrical and Computer Engineering. Includes bibliographical references (p. 135-142).

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 94-103).

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 155-176). Available also in a digital version from Dissertation Abstracts.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 63-65). Also available in electronic version. Access restricted to campus users.