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Image data compression is an active topic of research in image processing. Traditionally, most image data compression schemes have been dominated by digital processing due to the fact that digital systems are inherently flexible and reliable. However, it has been demonstrated that optical processing can be used for spatial image data compression, using a method called interpolated differential pulse code modulation (IDPCM). This is a compression scheme which functions analogously with conventional digital DPCH compression, except that the specific compression steps are implemented by incoherent optical processing. The main objective of this research is to extend IDPCM to interframe compression, design such systems, and evaluate the compression performance limitation under no channel errors, given the subjectively acceptable image quality by means of digital simulation. We start with a review of digital spatial and interframe compression techniques and their implications for optical implementation. Then, the technological background of electro-optical devices which has made possible hybrid optical/digital processing for image data compression will be briefly discussed. Also, a detailed description of IDPCM coding is given, along with the ways that IDPCM can be extended to interframe compression. Finally, two architectures of hybrid and optical/digital interframe compression are proposed, simulated, and evaluated in order to discover potential performances of optically implemented interframe compression systems. Excellent reconstructed image quality is obtained by the proposed adaptive hybrid (O/D) IDPCM/frame replenishment technique at an overall transmission rate of 3 Mbits/sec, average bit rate of 1.5 bits/pixel, and the average compression ratio of 5.2:1.

The use of permutations in data compression is an aspect that is worthy of further exploration. The work that has been done in video compression based on permutations was primarily oriented towards lossless algorithms. The study of previous algorithms has led to a new algorithm that could be either lossless or lossy, for which the amount of compression and the quality of the output can be controlled. The lossless version of our algorithm performs close to lossy versions of H.264 and it improves on them for the majority of the videos that we analyzed. Our algorithm could be used in situations where there is a need for lossless compression and the video sequences are part of a single scene, e.g., medical videos, where loss of information could be risky or expensive. Some results on permutations, which may be of independent interest, arose in developing this algorithm. We report on these as well. / by Amalya Mihnea. / Thesis (Ph.D.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

by Patrick Chi-man Fung. / Thesis (M.Sc.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 57-58). / LIST OF FIGURES / LIST OF IMAGES / LIST OF TABLES / NOTATIONS / Chapter 1 --- INTRODUCTION --- p.1 / Chapter 2 --- THEORY --- p.3 / Chapter 2.1 --- Matrix Representation of LOT --- p.3 / Chapter 2.2 --- Feasibility of LOT --- p.5 / Chapter 2.3 --- Properties of Good Feasible LOT --- p.6 / Chapter 2.4 --- An Optimal LOT --- p.7 / Chapter 2.5 --- Approximation of an Optimal LOT --- p.10 / Chapter 2.6 --- Representation of an Approximately Optimal LOT --- p.13 / Chapter 3 --- IMPLEMENTATION --- p.17 / Chapter 3.1 --- Mathematical Background --- p.17 / Chapter 3.2 --- Analysis of LOT Flowgraph --- p.17 / Chapter 3.2.1 --- The Fundamental LOT Building Block --- p.17 / Chapter 3.2.2 --- +1/-1 Butterflies --- p.19 / Chapter 3.3 --- Conclusion --- p.25 / Chapter 4 --- RESULTS --- p.27 / Chapter 4.1 --- Objective of Energy Packing --- p.27 / Chapter 4.2 --- Nature of Target Images --- p.27 / Chapter 4.3 --- Methodology of LOT Coefficient Selection --- p.28 / Chapter 4.4 --- dB RMS Error in Pixel Values --- p.29 / Chapter 4.5 --- Negative Pixel Values in Reverse LOT --- p.30 / Chapter 4.6 --- LOT Coefficient Energy Distribution --- p.30 / Chapter 4.7 --- Experimental Data --- p.32 / Chapter 5 --- DISCUSSION AND CONCLUSIONS --- p.46 / Chapter 5.1 --- RMS Error (dB) and LOT Coeffs. Drop Ratio --- p.46 / Chapter 5.1.1 --- Numeric Experimental Results --- p.46 / Chapter 5.1.2 --- Human Visual Response --- p.46 / Chapter 5.1.3 --- Conclusion --- p.49 / Chapter 5.2 --- Number of Negative Pixel Values in RLOT --- p.50 / Chapter 5.3 --- LOT Coefficient Energy Distribution --- p.51 / Chapter 5.4 --- Effect of Changing the Block Size --- p.54 / REFERENCES --- p.57 / APPENDIX / Tables of Experimental Data --- p.59

Thesis (Elec.E)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaves 173-175. / by Samuel Holtzman Dantus. / Elec.E

Thesis. 1977. M.S.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by Joseph Y. N. Hui. / M.S.

This thesis is a preliminary study of the relative performance of the major speech compression techniques, Differential Pulse Code Modulation (DPCM) and Subband Coding (SBC) in the presence of transmission distortion. The combined effect of the channel distortions and the channel codec including error correction is represented by bursts of bit errors. While compression is critical since bandwidth is scarce in a wireless channel, channel distortions are greater and less predictable. Little to no work has addressed the impact of channel errors on perceptual quality of speech due to the complexity of the problem. At the transmitter, the input signal is compressed to 24 kbps using either DPCM or SBC, quantized, binary encoded and transmitted over the burst error channel. The reverse process is carried out at the receiver. DPCM achieves compression by removing redundant information in successive time domain samples, while SBC uses lower resolution quantizer to encode frequency bands of lower perceptual importance. The performance of these codecs is evaluated for BERs of 0.001 and 0.05, with the burst lengths varying between 4 and 64 bits. Two different speech segments - one voiced and one unvoiced are used in testing. Performance measures include two objective tests signal to noise ratio (SNR) & segmental SNR, and a subjective test of perceptual quality - the Mean Opinion Score (MOS). The results obtained show that with a fixed BER and increasing burst length in bits, the total errors reduce in the decoded speech thereby improving its perceptual quality for both DPCM and SBC. Informal subjective tests also demonstrate this trend as well as indicate distortion in DPCM seemed to be less perceptually degrading than SBC. / Graduation date: 1999

Webster Pope Dove. / Originally published as thesis (Dept. of Electrical Engineering and Computer Science, M.S., 1980). / Bibliography: leaf 150. / National Science Foundation Grant ENG76-24117 National Science Foundation Grant ECS79-15226