A Histogram Modification Framework and Its Application for Image Contrast Enhancement
T.Arici,S.Dikbas,Y.Altunbasak, IEEE transactions on Image Processing,Vol.18,no.9,Sep 2009
This paper deals with histogram modification to enhance the image contrast to obtain visually pleasing images that has low computational complexity and that could be easily implemented in FPGAs.
To enhance the contrast, first the histogram of the image is obtained followed by the histogram equalization(HE). The HE finds a mapping to obtain the image with the histogram that is as close as possible to uniform distribution to exploit the full dynamic range. This is called histogram modification.For the images with smooth background, the grey level differences in neighboring pixels looks like (spikes)noise.
The histogram spike problem can be solved at the beginning,if the histogram computation can be modified. This can be done by taking into account the pixels that have some level of contrast with their neighbors. The modified histogram represents the conditional probability of the pixel which is in contrast with its neighbors.
The level of enhancement can be adjusted to achieve natural looking of enhanced images. It is adjusted depending on the input image's contrast. Black and white stretching is performed , for dark images white stretching is done and for bright images black stretching is done.
Thus, the proposed method gives the level of controllability for contrast enhancement.It works well for both video and still images.
To enhance the contrast, first the histogram of the image is obtained followed by the histogram equalization(HE). The HE finds a mapping to obtain the image with the histogram that is as close as possible to uniform distribution to exploit the full dynamic range. This is called histogram modification.For the images with smooth background, the grey level differences in neighboring pixels looks like (spikes)noise.
The histogram spike problem can be solved at the beginning,if the histogram computation can be modified. This can be done by taking into account the pixels that have some level of contrast with their neighbors. The modified histogram represents the conditional probability of the pixel which is in contrast with its neighbors.
The level of enhancement can be adjusted to achieve natural looking of enhanced images. It is adjusted depending on the input image's contrast. Black and white stretching is performed , for dark images white stretching is done and for bright images black stretching is done.
Thus, the proposed method gives the level of controllability for contrast enhancement.It works well for both video and still images.