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Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization in the respect that the adaptive method computes several histograms, each corresponding to a distinct section of the image, and uses them to redistribute the lightness values of the image.
Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images. There are two ways to think about and implement histogram equalization, either as image change or as palette change.
DCT is to avoid the object with skin-like tone. Since human faces always have higher texture. Sobel operator or other operators can be applied to detect face edge. To position human features like eyes, using the projection and find the peak of the histogram of projection help to get the detail feature like mouth, hair, and lip.
An image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in a digital image. [1] It plots the number of pixels for each tonal value. By looking at the histogram for a specific image a viewer will be able to judge the entire tonal distribution at a glance.
A v-optimal histogram is based on the concept of minimizing a quantity which is called the weighted variance in this context. [1] This is defined as = =, where the histogram consists of J bins or buckets, n j is the number of items contained in the jth bin and where V j is the variance between the values associated with the items in the jth bin.
This method weighs the histogram, checks which of the two sides is heavier, and removes weight from the heavier side until it becomes the lighter. It repeats the same operation until the edges of the weighing scale meet. Given its simplicity, this method is a good choice as a first approach when presenting the subject of automatic image ...
The rate of adaptive evolution in the human genome has often been assumed to be constant over time. For example, the 35% estimate for α calculated by Fay et al. (2001) led them to conclude that there was one adaptive substitution in the human lineage every 200 years since human divergence from old-world monkeys. However, even if the original ...
Cognition refers to processes in human beings like perception, attention, learning, memory, thought, concept formation, reading, and problem solving. [40] Human visual processing is efficient in detecting changes and making comparisons between quantities, sizes, shapes and variations in lightness.