Nowadays, the popularity of digital devices especially for customer electronic products, such as monitor, television and camera increases. However, there are still some limitations in digital technology. Thus, some processing techniques are needed to improve the quality and increase the customers’ satisfaction. The objective of this project is to enhance the digital image, in term of brightness and contrast, while preserving the original mean brightness. In this project, point transformation and histogram manipulation techniques have been chosen to enhance contrast of image. There are 15 algorithms used in this project which are Image Negative, Log Transformation, Gamma Correction, Linear Contrast, Piecewise Contrast Stretching, Histogram Equalization (HE), Histogram Hyperbolization, Histogram Hyperbolization Bright, Histogram Specification to a Gaussian, Local Histogram Equalization, Brightness Preserving Bi-Histogram Equalization (BBHE), Dualistic Sub-Image Histogram Equalization (DSIHE), Recursive Mean-Separate Histogram Equalization (RMSHE), Brightness Preserving Histogram Equalization with Maximum Entropy (BPHEME) and Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE). In this project, three measurements had been used to compare the results. These measurements are Absolute Mean Brightness Error (AMBE), Minimum Absolute Mean Brightness Error (MAMBE) and Entropy Measurement. Results from our investigation have shown that the best contrast enhancement algorithm among the algorithms tested which can be used to enhance the digital image in term of brightness and contrast, while preserving the original mean brightness, is Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE).
.
IMAGE ENHANCEMENT USING PIXEL BASED TRANSFORMATION_Lim Ing Ann_E3_2007_875003040_NI