我已经搜索了如何通过代码在 android 中对图像进行像素化,结果各不相同。
我在此处找到了有关如何应用其他效果的库和教程:http: //xjaphx.wordpress.com/learning/tutorials/
有人可以为我澄清一下吗,在android中动态像素化图像的最简单方法是什么
如果它是一个我可以进行多少轮或我想要图像像素化多少的功能,它也会很方便。
预先感谢。
我已经搜索了如何通过代码在 android 中对图像进行像素化,结果各不相同。
我在此处找到了有关如何应用其他效果的库和教程:http: //xjaphx.wordpress.com/learning/tutorials/
有人可以为我澄清一下吗,在android中动态像素化图像的最简单方法是什么
如果它是一个我可以进行多少轮或我想要图像像素化多少的功能,它也会很方便。
预先感谢。
像素化图像的最简单方法是使用“最近邻”算法缩小图像,然后使用相同的算法放大图像。
过滤图像试图找到一个平均值需要更多的时间,但实际上并没有对结果质量产生任何改进,毕竟你是故意想让你的图像失真的。
我以前在 vb.net 中做过这个,它很容易变成一个函数,它的参数可以控制你想要的像素化程度。
基本思想是以X宽和y高的块为单位扫描图像。对于每个块,您找到平均 RGB 值并将所有这些像素设置为该颜色。块尺寸越小,像素化越少。
int avR,avB,avG; // store average of rgb
int pixel;
Bitmap bmOut = Bitmap.createBitmap(width, height, src.getConfig());
for(int x = 0; x < width; x+= pixelationAmount) { // do the whole image
for(int y = 0; y < height; y++ pixelationamount) {
avR = 0; avG = 0; avB =0;
for(int xx =x; xx <pixelationAmount;xx++){// YOU WILL WANT TO PUYT SOME OUT OF BOUNDS CHECKING HERE
for(int yy= y; yy <pixelationAmount;yy++){ // this is scanning the colors
pixel = src.getPixel(x, y);
avR += (int) (color.red(pixel);
avG+= (int) (color.green(pixel);
avB += (int) (color.blue(pixel);
}
}
avrR/= pixelationAmount^2; //divide all by the amount of samples taken to get an average
avrG/= pixelationAmount^2;
avrB/= pixelationAmount^2;
for(int xx =x; xx <pixelationAmount;xx++){// YOU WILL WANT TO PUYT SOME OUT OF BOUNDS CHECKING HERE
for(int yy= y; yy <pixelationAmount;yy++){ // this is going back over the block
bmOut.setPixel(xx, yy, Color.argb(255, avR, avG,avB)); //sets the block to the average color
}
}
}
}
对错误的格式感到抱歉(很快在记事本中写了),但认为它可能会给你一个框架来制作你自己的像素化功能
这是对上述有效算法的纠正:
Bitmap bmOut = Bitmap.createBitmap(OriginalBitmap.getWidth(),OriginalBitmap.getHeight(),OriginalBitmap.getConfig());
int pixelationAmount = 50; //you can change it!!
int width = OriginalBitmap.getWidth();
int height = OriginalBitmap.getHeight();
int avR,avB,avG; // store average of rgb
int pixel;
for(int x = 0; x < width; x+= pixelationAmount) { // do the whole image
for(int y = 0; y < height; y+= pixelationAmount) {
avR = 0; avG = 0; avB =0;
int bx = x + pixelationAmount;
int by = y + pixelationAmount;
if(by >= height) by = height;
if(bx >= width)bx = width;
for(int xx =x; xx < bx;xx++){// YOU WILL WANT TO PUYT SOME OUT OF BOUNDS CHECKING HERE
for(int yy= y; yy < by;yy++){ // this is scanning the colors
pixel = OriginalBitmap.getPixel(xx, yy);
avR += (int) (Color.red(pixel));
avG+= (int) (Color.green(pixel));
avB += (int) (Color.blue(pixel));
}
}
avR/= pixelationAmount^2; //divide all by the amount of samples taken to get an average
avG/= pixelationAmount^2;
avB/= pixelationAmount^2;
for(int xx =x; xx < bx;xx++)// YOU WILL WANT TO PUYT SOME OUT OF BOUNDS CHECKING HERE
for(int yy= y; yy <by;yy++){ // this is going back over the block
bmOut.setPixel(xx, yy, Color.argb(255, avR, avG,avB)); //sets the block to the average color
}
}
}
iv.setImageBitmap(bmOut);
无论如何,这不是我想要的
我已经完全改变了以前的算法,它真的做了像马赛克过滤器这样的事情!这个想法是用下面的块像素替换每个块像素,简单地使用这个函数:
public void filter(){
Bitmap bmOut = Bitmap.createBitmap(OriginalBitmap.getWidth(),OriginalBitmap.getHeight(),OriginalBitmap.getConfig());
int pixelationAmount = 10;
Bitmap a = Bitmap.createBitmap(pixelationAmount,pixelationAmount,OriginalBitmap.getConfig());
Bitmap b = Bitmap.createBitmap(pixelationAmount,pixelationAmount,OriginalBitmap.getConfig());
int width = OriginalBitmap.getWidth();
int height = OriginalBitmap.getHeight();
int pixel;
int counter = 1;
int px = 0;int py = 0;int pbx=0;int pby=0;
for(int x = 0; x < width; x+= pixelationAmount) { // do the whole image
for(int y = 0; y < height; y+= pixelationAmount) {
int bx = x + pixelationAmount;
int by = y + pixelationAmount;
if(by >= height) by = height;
if(bx >= width)bx = width;
int xxx = -1;
int yyy = -1;
for(int xx =x; xx < bx;xx++){// YOU WILL WANT TO PUYT SOME OUT OF BOUNDS CHECKING HERE
xxx++;
yyy = -1;
for(int yy= y; yy < by;yy++){ // this is scanning the colors
yyy++;
pixel = OriginalBitmap.getPixel(xx, yy);
if(counter == 1)
{
a.setPixel(xxx, yyy, pixel);
px = x;//previous x
py = y;//previous y
pbx = bx;
pby = by;
}
else
b.setPixel(xxx, yyy, pixel);
}
}
counter++;
if(counter == 3)
{
int xxxx = -1;
int yyyy = -1;
for(int xx =x; xx < bx;xx++)
{
xxxx++;
yyyy = -1;
for(int yy= y; yy <by;yy++){
yyyy++;
bmOut.setPixel(xx, yy, b.getPixel(xxxx, yyyy));
}
}
for(int xx =px; xx < pbx;xx++)
{
for(int yy= py; yy <pby;yy++){
bmOut.setPixel(xx, yy, a.getPixel(xxxx, yyyy)); //sets the block to the average color
}
}
counter = 1;
}
}
}
image_view.setImageBitmap(bmOut);
}
这是我使用的代码:
ImageFilter 是父类:
public abstract class ImageFilter {
protected int [] pixels;
protected int width;
protected int height;
public ImageFilter (int [] _pixels, int _width,int _height){
setPixels(_pixels,_width,_height);
}
public void setPixels(int [] _pixels, int _width,int _height){
pixels = _pixels;
width = _width;
height = _height;
}
/**
* a weighted Euclidean distance in RGB space
* @param c1
* @param c2
* @return
*/
public double colorDistance(int c1, int c2)
{
int red1 = Color.red(c1);
int red2 = Color.red(c2);
int rmean = (red1 + red2) >> 1;
int r = red1 - red2;
int g = Color.green(c1) - Color.green(c2);
int b = Color.blue(c1) - Color.blue(c2);
return Math.sqrt((((512+rmean)*r*r)>>8) + 4*g*g + (((767-rmean)*b*b)>>8));
}
public abstract int[] procImage();
}
public class PixelateFilter extends ImageFilter {
int pixelSize;
int[] colors;
/**
* @param _pixels
* @param _width
* @param _height
*/
public PixelateFilter(int[] _pixels, int _width, int _height) {
this(_pixels, _width, _height, 10);
}
public PixelateFilter(int[] _pixels, int _width, int _height, int _pixelSize) {
this(_pixels, _width, _height, _pixelSize, null);
}
public PixelateFilter(int[] _pixels, int _width, int _height, int _pixelSize, int[] _colors) {
super(_pixels, _width, _height);
pixelSize = _pixelSize;
colors = _colors;
}
/* (non-Javadoc)
* @see imageProcessing.ImageFilter#procImage()
*/
@Override
public int[] procImage() {
for (int i = 0; i < width; i += pixelSize) {
for (int j = 0; j < height; j += pixelSize) {
int rectColor = getRectColor(i, j);
fillRectColor(rectColor, i, j);
}
}
return pixels;
}
private int getRectColor(int col, int row) {
int r = 0, g = 0, b = 0;
int sum = 0;
for (int x = col; x < col + pixelSize; x++) {
for (int y = row; y < row + pixelSize; y++) {
int index = x + y * width;
if (index < width * height) {
int color = pixels[x + y * width];
r += Color.red(color);
g += Color.green(color);
b += Color.blue(color);
}
}
}
sum = pixelSize * pixelSize;
int newColor = Color.rgb(r / sum, g / sum, b / sum);
if (colors != null)
newColor = getBestMatch(newColor);
return newColor;
}
private int getBestMatch(int color) {
double diff = Double.MAX_VALUE;
int res = color;
for (int c : colors) {
double currDiff = colorDistance(color, c);
if (currDiff < diff) {
diff = currDiff;
res = c;
}
}
return res;
}
private void fillRectColor(int color, int col, int row) {
for (int x = col; x < col + pixelSize; x++) {
for (int y = row; y < row + pixelSize; y++) {
int index = x + y * width;
if (x < width && y < height && index < width * height) {
pixels[x + y * width] = color;
}
}
}
}
public static final Bitmap changeToPixelate(Bitmap bitmap, int pixelSize, int [] colors) {
int width = bitmap.getWidth();
int height = bitmap.getHeight();
int[] pixels = new int[width * height];
bitmap.getPixels(pixels, 0, width, 0, 0, width, height);
PixelateFilter pixelateFilter = new PixelateFilter(pixels, width, height, pixelSize, colors);
int[] returnPixels = pixelateFilter.procImage();
Bitmap returnBitmap = Bitmap.createBitmap(returnPixels, width, height, Bitmap.Config.ARGB_8888);
return returnBitmap;
}
}
以下是你如何使用它:
int [] colors = new int [] { Color.BLACK,Color.WHITE,Color.BLUE,Color.CYAN,Color.RED};
final Bitmap bmOut = PixelateFilter.changeToPixelate(OriginalBitmap, pixelSize,colors);