Algorithm for The Assessment of Image Fidelity - Computer Science Assignment Help

Assignment Task

The visible differences predictor (VDP) is motivated by the need to quantitatively describe the visual consequences of decisions regarding the design and quality control of imaging products. Intended to be used in the development of image processing algorithms, imaging system hardware, and imaging media, it is a design tool that can find wide areas of application. The differences due to imaging systems may begin as mathematicaldifferences (i.e., incorrect code values), but ultimately end up as physical differences (i.e., incorrect luminances) once the image is displayed.

The goal of the VDP is to determine the degree to which these physical differences become visible dfl'erences. Commonly used techniques13 analyze parameters such as the system's MTF and noise power spectra, often with a one-dimensional integration, and calculate a single number describing image quality. While these techniques perform well for many aspects of analog media, they have not been as successful for describing digital image quality, the effects of adaptive algorithms, or the nonlinear aspects of analog media. The problems with these techniques lie in their lack of phase information in the analysis, their inability to deal effectively with nonlinearities, and their simplicity relative to the complexity of the visual system.

To solve these problems, the VDP uses a digital image processing approach. The use of two-dimensional images, rather than just parameters of the imaging system, enables the preservation of phase information. This information is necessary to predict visual distortion because of the masking properties of the visual system, in which the location of the image enor is as important as the magnitude. Further, nonimearities in the media or algorithms pose problems for the current approaches that use power spectra and MTF, because of their implications of linearity. An image processing approach can easily incorporate such systems parameters as MTF and noise power spectra through simulation, yet it also allows for more exact simulation of the nonlinearities of both the media and the visual system.

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