Date of Award

Spring 2007

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Electrical & Computer Engineering

Program/Concentration

Electrical Engineering

Committee Director

Vishnu K. Lakdawala

Committee Member

Linda Vahala

Committee Member

Min Song

Call Number for Print

Special Collections LD4331.E55 O76 2007

Abstract

Image enhancement is the processing of images to increase their usefulness. The image enhancement methods and objectives vary with the application. When images are enhanced for human viewers, as in television, the objective is mostly to improve perceptual aspects: image quality, intelligibility, or visual appearance. The aim of this research work is to make the processed image better in the visual sense than the unprocessed image. An image can often be enhanced by modifying its contrast or dynamic range, increasing the sharpness of edges, reducing the noise, or reducing the blurring. The most commonly used contrast enhancement technique is histogram modification. In many cases, the subjective contrast of an image is improved if one equilizes the histogram of the gray levels of the picture elements (pixels). In this thesis a method for reducing noise and enhancing edges and thus enhancing the resolution of the image is presented. Noise removal is done through vector median filtering. The median filter performs a nonlinear filtering operation where a window moves over an image. At each location the pixel with the smallest norm with respect to other pixels within the window is chosen as the vector median and the output value of the pixel at that location. The edge enhancement procedure is done through increasing the sharpness of edges by a nonlinear procedure that uses shape invariant properties of edges across scale and utilizes Laplacian transform and Laplacian pyramid image representation.

The experiments performed on various images captured at low and non uniform environment show promising results. The details of the high frequency regions of the images are improved significantly by the proposed method. Research work is progressing to adapt the algorithm to make it suitable for enhancing images based on the statistical characteristics of the objects to be recognized.

Rights

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DOI

10.25777/qes1-6014

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