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java image enlargement and reduction

黄舟

Release： 2016-12-30 11:51:04

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To enlarge the image, you need to supplement the missing pixels. Commonly used methods are

1. Nearest Neighbor algorithm (Nearest Neighbor)

2. Bilinear interpolation algorithm (Bilinear Interpolation )

3. Bicubic Interpolation Algorithm (Bicubic Interpolation)

Wait, please see (Image Magnification Algorithm) for detailed introduction
Now we will use the nearest neighbor point interpolation method to magnify the image The effect of twice the code

<span style="font-size:14px;"><span style="font-size:10px;">p<span style="font-family:Courier New;">ublic void Todouble(){
		int[] doubleData = new int[2*w*2*h];
		for (int y = 0; y < h; y++) {
            for (int x = 0; x < w; x++) {
            	doubleData[2*x + 2*y *2* w] = data[x + y * w];
            }
		}
		
		this.h = 2*h;
		this.w = 2*w;
		for (int y = 0; y < h; y++) {
            for (int x = 0; x < w; x++) {
            	if(y%2 == 1)
            		doubleData[x + y*w] = doubleData[x + (y-1)*w];
            	if(x%2 == 1)
            		doubleData[x + y*w] = doubleData[x-1 + y*w];
            }
		}
		this.data = doubleData;
		
	}</span></span></span>

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is as follows:

java image enlargement and reduction

## Reduction is relatively simple, and reduction is to remove some pixels.

Minified code:

<span   style="max-width:90%"><span style="font-size:10px;">public void reduce(int a){//a是缩小的<span style="font-family:Times New Roman;">倍数</span>
		int nw = w/a;
		int nh = h/a;
		int[] d = new int[nw*nh];
		
		for (int y = 0; y < nh; y++) {
                  for (int x = 0; x < nw; x++) {
            	   d[x + y*nw] = data[a*x + a*y * w];
                  }
		}
		this.h = nh;
		this.w = nw;
		this.data = d;
	}</span></span>

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The running effect is as follows:

java image enlargement and reduction

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