Flat panel display signal processing

Televisions (TVs) have shown considerable technological progress since their introduction almost a century ago. Starting out as small, dim and monochrome screens in wooden cabinets, TVs have evolved to large, bright and colorful displays in plastic boxes. It took until the turn of the century, however, for the TV to become like a ‘picture on the wall’. This happened when the bulky Cathode Ray Tube (CRT) was replaced with thin and light-weight Flat Panel Displays (FPDs), such as Liquid Crystal Displays (LCDs) or Plasma Display Panels (PDPs). However, the TV system and transmission formats are still strongly coupled to the CRT technology, whereas FPDs use very different principles to convert the electronic video signal to visible images. These differences result in image artifacts that the CRT never had, but at the same time provide opportunities to improve FPD image quality beyond that of the CRT. This thesis presents an analysis of the properties of flat panel displays, their relation to image quality, and video signal processing algorithms to improve the quality of the displayed images. To analyze different types of displays, the display signal chain is described using basic principles common to all displays. The main function of a display is to create visible images (light) from an electronic signal (video), requiring display chain functions like opto-electronic effect, spatial and temporal addressing and reconstruction, and color synthesis. The properties of these functions are used to describe CRT, LCDs, and PDPs, showing that these displays perform the same functions, using different implementations. These differences have a number of consequences, that are further investigated in this thesis. Spatial and temporal aspects, corresponding to ‘static’ and ‘dynamic’ resolution respectively, are covered in detail. Moreover, video signal processing is an essential part of the display signal chain for FPDs, because the display format will in general no longer match the source format. In this thesis, it is investigated how specific FPD properties, especially related to spatial and temporal addressing and reconstruction, affect the video signal processing chain. A model of the display signal chain is presented, and applied to analyze FPD spatial properties in relation to static resolution. In particular, the effect of the color subpixels, that enable color image reproduction in FPDs, is analyzed. The perceived display resolution is strongly influenced by the color subpixel arrangement. When taken into account in the signal chain, this improves the perceived resolution on FPDs, which clearly outperform CRTs in this respect. The cause and effect of this improvement, also for alternative subpixel arrangements, is studied using the display signal model. However, the resolution increase cannot be achieved without video processing. This processing is efficiently combined with image scaling, which is always required in the FPD display signal chain, resulting in an algorithm called ‘subpixel image scaling’. A comparison of the effects of subpixel scaling on several subpixel arrangements shows that the largest increase in perceived resolution is found for two-dimensional subpixel arrangements. FPDs outperform CRTs with respect to static resolution, but not with respect to ‘dynamic resolution’, i.e. the perceived resolution of moving images. Life-like reproduction of moving images is an important requirement for a TV display, but the temporal properties of FPDs cause artifacts in moving images (‘motion artifacts’), that are not found in CRTs. A model of the temporal aspects of the display signal chain is used to analyze dynamic resolution and motion artifacts on several display types, in particular LCD and PDP. Furthermore, video signal processing algorithms are developed that can reduce motion artifacts and increase the dynamic resolution. The occurrence of motion artifacts is explained by the fact that the human visual system tracks moving objects. This converts temporal effects on the display into perceived spatial effects, that can appear in very different ways. The analysis shows how addressing mismatches in the chain cause motion-dependent misalignment of image data, e.g. resulting in the ‘dynamic false contour’ artifact in PDPs. Also, non-ideal temporal reconstruction results in ‘motion blur’, i.e. a loss of sharpness of moving images, which is typical for LCDs. The relation between motion blur, dynamic resolution, and temporal properties of LCDs is analyzed using the display signal model in the temporal (frequency) domain. The concepts of temporal aperture, motion aperture and temporal display bandwidth are introduced, which enable characterization of motion blur in a simple and direct way. This is applied to compare several motion blur reduction methods, based on modified display design and driving. This thesis further describes the development of several video processing algorithms that can reduce motion artifacts. It is shown that the motion of objects in the image plays an essential role in these algorithms, i.e. they require motion estimation and compensation techniques. In LCDs, video processing for motion artifact reduction involves a compensation for the temporal reconstruction characteristics of the display, leading to the ‘motion compensated inverse filtering’ algorithm. The display chain model is used to analyze this algorithm, and several methods to increase its performance are presented. In PDPs, motion artifact reduction can be achieved with ‘motion compensated subfield generation’, for which an advanced algorithm is presented

Video guidance, landing, and imaging systems

The adaptive potential of video guidance technology for earth orbital and interplanetary missions was explored. The application of video acquisition, pointing, tracking, and navigation technology was considered to three primary missions: planetary landing, earth resources satellite, and spacecraft rendezvous and docking. It was found that an imaging system can be mechanized to provide a spacecraft or satellite with a considerable amount of adaptability with respect to its environment. It also provides a level of autonomy essential to many future missions and enhances their data gathering ability. The feasibility of an autonomous video guidance system capable of observing a planetary surface during terminal descent and selecting the most acceptable landing site was successfully demonstrated in the laboratory. The techniques developed for acquisition, pointing, and tracking show promise for recognizing and tracking coastlines, rivers, and other constituents of interest. Routines were written and checked for rendezvous, docking, and station-keeping functions

Cognitive Information Processing

Contains research objectives and summary of research on fourteen research projects and reports on four research projects.Joint Services Electronics Program (Contract DAAB07-75-C-1346)National Science Foundation (Grant EPP74-12653)National Science Foundation (Grant ENG74-24344)National Institutes of Health (Grant 2 PO1 GM19428-04)Swiss National Funds for Scientific ResearchM.I.T. Health Sciences Fund (Grant 76-11)National Institutes of Health (Grant F03 GM58698)National Institutes of Health (Biomedical Sciences Support Grant)Associated Press (Grant

Evaluation of the color image and video processing chain and visual quality management for consumer systems

With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video

Video Guidance, Landing, and Imaging system (VGLIS) for space missions

The feasibility of an autonomous video guidance system that is capable of observing a planetary surface during terminal descent and selecting the most acceptable landing site was demonstrated. The system was breadboarded and "flown" on a physical simulator consisting of a control panel and monitor, a dynamic simulator, and a PDP-9 computer. The breadboard VGLIS consisted of an image dissector camera and the appropriate processing logic. Results are reported

Contrast Image Enhancement By Gamma Correction

One of the important techniques in digital image processing is to enhance images. Contrast enhancement is a method that is used to enhance images for viewing process or for further analysis of images. Main idea behind contrast enhancement techniques is to increase contrast and to preserve original brightness of images. In this  a project  contrast enhancement technique  called Gamma correction is used for this purpose . The value of the Gamma affects the result of the contrast of the image, the larger the light increases, the smaller the light decrease . the best value is " 2.2 " Keywords: digital image processing , Image Enhancement

On the implementation of the gamma function for image correction on a endoscopic camera

This paper describes part of project that implemented the image processing of a CMOS sensor for endoscopic purposes. The sensor is a small sized device of 1x1mm2 and the image processing has been done inside a FPGA. This part of the work describes the implementation of the Gamma function with a balance between the resources needed and the accuracy. A linear piecewise solution was used that stores the values for 31 gamma functions with values ranging from 1 to 4 with 0.1 steps. The solution developed is 10 bit based, was coded in VHDL and is implemented in a Spartan 6 FPGA. The results show that it is an accurate solution that has a small footprint in terms of used resources.info:eu-repo/semantics/publishedVersio

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

Layer Decomposition Learning Based on Gaussian Convolution Model and Residual Deblurring for Inverse Halftoning

Layer decomposition to separate an input image into base and detail layers has been steadily used for image restoration. Existing residual networks based on an additive model require residual layers with a small output range for fast convergence and visual quality improvement. However, in inverse halftoning, homogenous dot patterns hinder a small output range from the residual layers. Therefore, a new layer decomposition network based on the Gaussian convolution model (GCM) and structure-aware deblurring strategy is presented to achieve residual learning for both the base and detail layers. For the base layer, a new GCM-based residual subnetwork is presented. The GCM utilizes a statistical distribution, in which the image difference between a blurred continuous-tone image and a blurred halftoned image with a Gaussian filter can result in a narrow output range. Subsequently, the GCM-based residual subnetwork uses a Gaussian-filtered halftoned image as input and outputs the image difference as residual, thereby generating the base layer, i.e., the Gaussian-blurred continuous-tone image. For the detail layer, a new structure-aware residual deblurring subnetwork (SARDS) is presented. To remove the Gaussian blurring of the base layer, the SARDS uses the predicted base layer as input and outputs the deblurred version. To more effectively restore image structures such as lines and texts, a new image structure map predictor is incorporated into the deblurring network to induce structure-adaptive learning. This paper provides a method to realize the residual learning of both the base and detail layers based on the GCM and SARDS. In addition, it is verified that the proposed method surpasses state-of-the-art methods based on U-Net, direct deblurring networks, and progressively residual networks