Title

Comparison of Two Image Enhancement Techniques: Histogram Equalization and Gamma Method

School Name

Blythewood High School

Grade Level

11th Grade

Presentation Topic

Computer Science

Presentation Type

Non-Mentored

Abstract

Two image enhancement methods are compared: histogram equalization (HE) method and gamma or power law method. Intensity transformations are among the simplest of all image processing techniques. In HE method, pixels of the image occupy the entire range of possible intensity levels, which results in high contrast. In gamma method, fractional values of gamma map a narrow range of dark input values into a wider range of output values. We claimed that the rate of success for HE method is greater than that from the gamma method. Using the p-value we failed to reject the null hypothesis at significance level (α) = .05, suggesting there is no sufficient evidence to support the claim that the rate of success for HE method is greater than that from the gamma method.

Location

Founders Hall 140 B

Start Date

3-30-2019 10:00 AM

Presentation Format

Oral and Written

Group Project

No

COinS
 
Mar 30th, 10:00 AM

Comparison of Two Image Enhancement Techniques: Histogram Equalization and Gamma Method

Founders Hall 140 B

Two image enhancement methods are compared: histogram equalization (HE) method and gamma or power law method. Intensity transformations are among the simplest of all image processing techniques. In HE method, pixels of the image occupy the entire range of possible intensity levels, which results in high contrast. In gamma method, fractional values of gamma map a narrow range of dark input values into a wider range of output values. We claimed that the rate of success for HE method is greater than that from the gamma method. Using the p-value we failed to reject the null hypothesis at significance level (α) = .05, suggesting there is no sufficient evidence to support the claim that the rate of success for HE method is greater than that from the gamma method.