Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity

A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm. A dual mathematical interpretation of the proposed framework with structured sparse estimation is described, which shows that the resulting piecewise linear estimate stabilizes the estimation when compared to traditional sparse inverse problem techniques. This interpretation also suggests an effective dictionary motivated initialization for the MAP-EM algorithm. We demonstrate that in a number of image inverse problems, including inpainting, zooming, and deblurring, the same algorithm produces either equal, often significantly better, or very small margin worse results than the best published ones, at a lower computational cost.Comment: 30 page

Design of a digital compression technique for shuttle television

The determination of the performance and hardware complexity of data compression algorithms applicable to color television signals, were studied to assess the feasibility of digital compression techniques for shuttle communications applications. For return link communications, it is shown that a nonadaptive two dimensional DPCM technique compresses the bandwidth of field-sequential color TV to about 13 MBPS and requires less than 60 watts of secondary power. For forward link communications, a facsimile coding technique is recommended which provides high resolution slow scan television on a 144 KBPS channel. The onboard decoder requires about 19 watts of secondary power

A receiver-compatible noise reduction system

Also issued as Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1990.Includes bibliographical references (p. 111-113).Supported in part by the National Science Foundation. MIP 87-14969 Supported in part by the Maryland Procurement Office. MDA 904-89-C-3009Matthew M. Bace

Digital encoding of black and white facsimile signals

As the costs of digital signal processing and memory hardware are decreasing each year compared to those of transmission, it is increasingly economical to apply sophisticated source encoding techniques to reduce the transmission time for facsimile documents. With this intent, information lossy encoding schemes have been investigated in which the encoder is divided into two stages. Firstly, preprocessing, which removes redundant information from the original documents, and secondly, actual encoding of the preprocessed documents. [Continues.

Modeling the television process

Also issued as Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1986.Includes bibliographical references.Supported in part by members of the Center for Advanced Television Studies.Michael Anthony Isnardi

Current video compression algorithms: Comparisons, optimizations, and improvements

Compression algorithms have evolved significantly in recent years. Audio, still image, and video can be compressed significantly by taking advantage of the natural redundancies that occur within them. Video compression in particular has made significant advances. MPEG-1 and MPEG-2, two of the major video compression standards, allowed video to be compressed at very low bit rates compared to the original video. The compression ratio for video that is perceptually lossless (losses can\u27t be visually perceived) can even be as high as 40 or 50 to 1 for certain videos. Videos with a small degradation in quality can be compressed at 100 to 1 or more; Although the MPEG standards provided low bit rate compression, even higher quality compression is required for efficient transmission over limited bandwidth networks, wireless networks, and broadcast mediums. Significant gains have been made over the current MPEG-2 standard in a newly developed standard called the Advanced Video Coder, also known as H.264 and MPEG-4 part 10. (Abstract shortened by UMI.)

A Vision-Based Technique for Lay Length Measurement of Metallic Wire Ropes

The lay length of metallic wire ropes is an important dimensional quantity whose analysis is useful to highlight rope deformations due to distributed damages. This paper describes a measurement system that is based on a video camera and on an offline processing algorithm. The camera acquires an image sequence of the running rope; then, an image processing algorithm extracts the rope contour and measures both the distance among rope strands and the whole distance covered by the rope during the test. A mathematical model of the rope contour has been developed and employed to test the proposed algorithm with simulated data. Field tests have been carried out with the proposed system on a working aerial cableway using a general-purpose camer