22-03-2014, 03:00 PM
Quadrants dynamic histogram equalisation for contrast enhancement
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Introduction
The quality of the images captured in dark environment using cell phone camera is usually poor as a result of low contrast
To overcome this drawback ,light emitting diodes are used to assist the dark environment.
Moreover , the lighting from LEDs reflected during capturing the image involves transparent glasses .
In these cases , the image captured produces annoying artifacts as a result of low contrast
For contrast enhancement ,histogram equalisation is a simple and widely used.
QDHE
QDHE algorithm separates the into four(quadrant) sub-histograms based on the median of the input image.
The resultant sub-histograms are clipped according to the mean intensity occurrence of input image before new dynamic range assigned and equalise the each sub-histogram.
The QDHE consists of four processes , namely
Histogram partitioning
Clipping
Gray level range allocation
Histogram equalisation
Objectives
Study of Histogram equalisation techniques
Study of Contrast enhancement techniques
Study of QDHE algorithm
Implementation of this algorithm using matlab
clipping
Clipping process is to control the enhancement rate of Histogram Equalization in order to overcome unnatural and over enhancement of the processed image to occur.
A clipping threshold value is set to the histogram as Tc is the average of the number of intensity values.