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Image histogram equalization algorithm
Histogram equalization is a fundamental technique in image processing that enhances contrast by adjusting the distribution of intensity levels. Its goal is to redistribute brightness values more evenly across the available dynamic range, highlighting details in overly dark or bright areas. This method transforms the original image’s histogram into an approximately uniform distribution, making it valuable for applications such as medical image analysis, computer vision, and photo enhancement.
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How does histogram equalization work?
histogram equalization transforms the intensity values of an image to achieve a more uniform distribution. The process consists of the following steps.
- Compute the histogram: the image’s histogram is obtained, showing the frequency of each grayscale level.
- Compute the cumulative distribution function (CDF): The CDF is calculated, representing the accumulated probability of intensity levels.
- Normalize the CDF: The CDF is divided by the number of pixels to scale it to an appropriate range.
- Reassign intensity values: The normalized CDF is used to reassign pixel intensity values…
