Last time I try to compressed image file with quantization method. Why quantization? Because this method is more easily than other….he…he… I try with two kind of image file. First is grayscale image and the second is RGB image. Grayscale image have a simple digital data, that consist grayscale degree in each pixels (2D matrix). With quantization method we can decrease bit that represent grayscale degree. For example we have 6x6 pixel grayscale image, and each pixel represent with 8 bit. We want to decrease from 8 bit to 4 bit to represent each pixel. So we made a table that convert each value of initial grayscale degree to compressed grayscale degree. We change each value with other value according this table. If we have a RGB file it’s similar with grayscale image. But from RGB image we have 3D matrix that represent width, height and RGB factor. We can consider it as three matrix 2D, namely for R factor, G factor and B factor. Each of matrix consist of R or G or B degree of image. If in initial image three kind of matrix represent with 256 bit and we want to reduce it into 128 bit, so we do it same with in grayscale image. I implemented that method in matlab. I also compare image histogram before an after compression that give in above.
Image and histogram before and after compression in RGB image
Image and histogram before and after compression in grayscale image 
1 komentar:
whoa big words much, you need to make it so that retards, like me, are able to read past the first sentence! lmao
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