1.图片处理
1.圆角图片
复制代码 代码如下:
/**
* 转换成圆角
*
* @param bmp
* @param roundpx
* @return
*/
public static bitmap converttoroundedcorner(bitmap bmp, float roundpx) {
bitmap newbmp = bitmap.createbitmap(bmp.getwidth(), bmp.getheight(),
config.argb_8888);
// 得到画布
canvas canvas = new canvas(newbmp);
final int color = 0xff424242;
final paint paint = new paint();
final rect rect = new rect(0, 0, bmp.getwidth(), bmp.getheight());
final rectf rectf = new rectf(rect);
paint.setantialias(true);
canvas.drawargb(0, 0, 0, 0);
paint.setcolor(color);
// 第二个和第三个参数一样则画的是正圆的一角，否则是椭圆的一角
canvas.drawroundrect(rectf, roundpx, roundpx, paint);
paint.setxfermode(new porterduffxfermode(mode.src_in));
canvas.drawbitmap(bmp, rect, rect, paint);
return newbmp;
}
2.滤镜效果
1.黑白效果
复制代码 代码如下:
/**
* 将彩色图转换为黑白图
*
* @param 位图
* @return 返回转换好的位图
*/
public static bitmap converttoblackwhite(bitmap bmp) {
int width = bmp.getwidth(); // 获取位图的宽
int height = bmp.getheight(); // 获取位图的高
int[] pixels = new int[width * height]; // 通过位图的大小创建像素点数组
bmp.getpixels(pixels, 0, width, 0, 0, width, height);
int alpha = 0xff << 24;
for (int i = 0; i < height; i++) {
for (int j = 0; j < width; j++) {
int grey = pixels[width * i + j];
int red = ((grey & 0x00ff0000) >> 16);
int green = ((grey & 0x0000ff00) >> 8);
int blue = (grey & 0x000000ff);
grey = (int) (red * 0.3 + green * 0.59 + blue * 0.11);
grey = alpha | (grey << 16) | (grey << 8) | grey;
pixels[width * i + j] = grey;
}
}
bitmap newbmp = bitmap.createbitmap(width, height, config.rgb_565);
newbmp.setpixels(pixels, 0, width, 0, 0, width, height);
return newbmp;
}
2.高斯模糊
复制代码 代码如下:
/**
* 高斯模糊
*
* @param bmp
* @return
*/
public static bitmap converttoblur(bitmap bmp) {
// 高斯矩阵
int[] gauss = new int[] { 1, 2, 1, 2, 4, 2, 1, 2, 1 };
int width = bmp.getwidth();
int height = bmp.getheight();
bitmap newbmp = bitmap.createbitmap(width, height,
bitmap.config.rgb_565);
int pixr = 0;
int pixg = 0;
int pixb = 0;
int pixcolor = 0;
int newr = 0;
int newg = 0;
int newb = 0;
int delta = 16; // 值越小图片会越亮，越大则越暗
int idx = 0;
int[] pixels = new int[width * height];
bmp.getpixels(pixels, 0, width, 0, 0, width, height);
for (int i = 1, length = height - 1; i < length; i++) {
for (int k = 1, len = width - 1; k < len; k++) {
idx = 0;
for (int m = -1; m <= 1; m++) {
for (int n = -1; n <= 1; n++) {
pixcolor = pixels[(i + m) * width + k + n];
pixr = color.red(pixcolor);
pixg = color.green(pixcolor);
pixb = color.blue(pixcolor);
newr = newr + pixr * gauss[idx];
newg = newg + pixg * gauss[idx];
newb = newb + pixb * gauss[idx];
idx++;
}
}
newr /= delta;
newg /= delta;
newb /= delta;
newr = math.min(255, math.max(0, newr));
newg = math.min(255, math.max(0, newg));
newb = math.min(255, math.max(0, newb));
pixels[i * width + k] = color.argb(255, newr, newg, newb);
newr = 0;
newg = 0;
newb = 0;
}
}
newbmp.setpixels(pixels, 0, width, 0, 0, width, height);
return newbmp;
}
3.素描效果
复制代码 代码如下:
/**
* 素描效果
*
* @param bmp
* @return
*/
public static bitmap converttosketch(bitmap bmp) {
int pos, row, col, clr;
int width = bmp.getwidth();
int height = bmp.getheight();
int[] pixsrc = new int[width * height];
int[] pixnvt = new int[width * height];
// 先对图象的像素处理成灰度颜色后再取反
bmp.getpixels(pixsrc, 0, width, 0, 0, width, height);
for (row = 0; row < height; row++) {
for (col = 0; col < width; col++) {
pos = row * width + col;
pixsrc[pos] = (color.red(pixsrc[pos])
+ color.green(pixsrc[pos]) + color.blue(pixsrc[pos])) / 3;
pixnvt[pos] = 255 - pixsrc[pos];
}
}
// 对取反的像素进行高斯模糊, 强度可以设置，暂定为5.0
gaussgray(pixnvt, 5.0, 5.0, width, height);
// 灰度颜色和模糊后像素进行差值运算
for (row = 0; row < height; row++) {
for (col = 0; col < width; col++) {
pos = row * width + col;
clr = pixsrc[pos] << 8;
clr /= 256 - pixnvt[pos];
clr = math.min(clr, 255);
pixsrc[pos] = color.rgb(clr, clr, clr);
}
}
bmp.setpixels(pixsrc, 0, width, 0, 0, width, height);
return bmp;
}
private static int gaussgray(int[] psrc, double horz, double vert,
int width, int height) {
int[] dst, src;
double[] n_p, n_m, d_p, d_m, bd_p, bd_m;
double[] val_p, val_m;
int i, j, t, k, row, col, terms;
int[] initial_p, initial_m;
double std_dev;
int row_stride = width;
int max_len = math.max(width, height);
int sp_p_idx, sp_m_idx, vp_idx, vm_idx;
val_p = new double[max_len];
val_m = new double[max_len];
n_p = new double[5];
n_m = new double[5];
d_p = new double[5];
d_m = new double[5];
bd_p = new double[5];
bd_m = new double[5];
src = new int[max_len];
dst = new int[max_len];
initial_p = new int[4];
initial_m = new int[4];
// 垂直方向
if (vert > 0.0) {
vert = math.abs(vert) + 1.0;
std_dev = math.sqrt(-(vert * vert) / (2 * math.log(1.0 / 255.0)));
// 初试化常量
findconstants(n_p, n_m, d_p, d_m, bd_p, bd_m, std_dev);
for (col = 0; col < width; col++) {
for (k = 0; k < max_len; k++) {
val_m[k] = val_p[k] = 0;
}
for (t = 0; t < height; t++) {
src[t] = psrc[t * row_stride + col];
}
sp_p_idx = 0;
sp_m_idx = height - 1;
vp_idx = 0;
vm_idx = height - 1;
initial_p[0] = src[0];
initial_m[0] = src[height - 1];
for (row = 0; row < height; row++) {
terms = (row < 4) ? row : 4;
for (i = 0; i <= terms; i++) {
val_p[vp_idx] += n_p[i] * src[sp_p_idx - i] - d_p[i]
* val_p[vp_idx - i];
val_m[vm_idx] += n_m[i] * src[sp_m_idx + i] - d_m[i]
* val_m[vm_idx + i];
}
for (j = i; j <= 4; j++) {
val_p[vp_idx] += (n_p[j] - bd_p[j]) * initial_p[0];
val_m[vm_idx] += (n_m[j] - bd_m[j]) * initial_m[0];
}
sp_p_idx++;
sp_m_idx--;
vp_idx++;
vm_idx--;
}
transfergausspixels(val_p, val_m, dst, 1, height);
for (t = 0; t < height; t++) {
psrc[t * row_stride + col] = dst[t];
}
}
}
// 水平方向
if (horz > 0.0) {
horz = math.abs(horz) + 1.0;
if (horz != vert) {
std_dev = math.sqrt(-(horz * horz)
/ (2 * math.log(1.0 / 255.0)));
// 初试化常量
findconstants(n_p, n_m, d_p, d_m, bd_p, bd_m, std_dev);
}
for (row = 0; row < height; row++) {
for (k = 0; k < max_len; k++) {
val_m[k] = val_p[k] = 0;
}
for (t = 0; t < width; t++) {
src[t] = psrc[row * row_stride + t];
}
sp_p_idx = 0;
sp_m_idx = width - 1;
vp_idx = 0;
vm_idx = width - 1;
initial_p[0] = src[0];
initial_m[0] = src[width - 1];
for (col = 0; col < width; col++) {
terms = (col < 4) ? col : 4;
for (i = 0; i <= terms; i++) {
val_p[vp_idx] += n_p[i] * src[sp_p_idx - i] - d_p[i]
* val_p[vp_idx - i];
val_m[vm_idx] += n_m[i] * src[sp_m_idx + i] - d_m[i]
* val_m[vm_idx + i];
}
for (j = i; j <= 4; j++) {
val_p[vp_idx] += (n_p[j] - bd_p[j]) * initial_p[0];
val_m[vm_idx] += (n_m[j] - bd_m[j]) * initial_m[0];
}
sp_p_idx++;
sp_m_idx--;
vp_idx++;
vm_idx--;
}
transfergausspixels(val_p, val_m, dst, 1, width);
for (t = 0; t < width; t++) {
psrc[row * row_stride + t] = dst[t];
}
}
}
return 0;
}
private static void transfergausspixels(double[] src1, double[] src2,
int[] dest, int bytes, int width) {
int i, j, k, b;
int bend = bytes * width;
double sum;
i = j = k = 0;
for (b = 0; b < bend; b++) {
sum = src1[i++] + src2[j++];
if (sum > 255)
sum = 255;
else if (sum < 0)
sum = 0;
dest[k++] = (int) sum;
}
}
private static void findconstants(double[] n_p, double[] n_m, double[] d_p,
double[] d_m, double[] bd_p, double[] bd_m, double std_dev) {
double div = math.sqrt(2 * 3.141593) * std_dev;
double x0 = -1.783 / std_dev;
double x1 = -1.723 / std_dev;
double x2 = 0.6318 / std_dev;
double x3 = 1.997 / std_dev;
double x4 = 1.6803 / div;
double x5 = 3.735 / div;
double x6 = -0.6803 / div;
double x7 = -0.2598 / div;
int i;
n_p[0] = x4 + x6;
n_p[1] = (math.exp(x1)
* (x7 * math.sin(x3) - (x6 + 2 * x4) * math.cos(x3)) + math
.exp(x0) * (x5 * math.sin(x2) - (2 * x6 + x4) * math.cos(x2)));
n_p[2] = (2
* math.exp(x0 + x1)
* ((x4 + x6) * math.cos(x3) * math.cos(x2) - x5 * math.cos(x3)
* math.sin(x2) - x7 * math.cos(x2) * math.sin(x3)) + x6
* math.exp(2 * x0) + x4 * math.exp(2 * x1));
n_p[3] = (math.exp(x1 + 2 * x0)
* (x7 * math.sin(x3) - x6 * math.cos(x3)) + math.exp(x0 + 2
* x1)
* (x5 * math.sin(x2) - x4 * math.cos(x2)));
n_p[4] = 0.0;
d_p[0] = 0.0;
d_p[1] = -2 * math.exp(x1) * math.cos(x3) - 2 * math.exp(x0)
* math.cos(x2);
d_p[2] = 4 * math.cos(x3) * math.cos(x2) * math.exp(x0 + x1)
+ math.exp(2 * x1) + math.exp(2 * x0);
d_p[3] = -2 * math.cos(x2) * math.exp(x0 + 2 * x1) - 2 * math.cos(x3)
* math.exp(x1 + 2 * x0);
d_p[4] = math.exp(2 * x0 + 2 * x1);
for (i = 0; i <= 4; i++) {
d_m[i] = d_p[i];
}
n_m[0] = 0.0;
for (i = 1; i <= 4; i++) {
n_m[i] = n_p[i] - d_p[i] * n_p[0];
}
double sum_n_p, sum_n_m, sum_d;
double a, b;
sum_n_p = 0.0;
sum_n_m = 0.0;
sum_d = 0.0;
for (i = 0; i <= 4; i++) {
sum_n_p += n_p[i];
sum_n_m += n_m[i];
sum_d += d_p[i];
}
a = sum_n_p / (1.0 + sum_d);
b = sum_n_m / (1.0 + sum_d);
for (i = 0; i <= 4; i++) {
bd_p[i] = d_p[i] * a;
bd_m[i] = d_m[i] * b;
}
}
4.锐化
复制代码 代码如下:
/**
* 图片锐化（拉普拉斯变换）
*
* @param bmp
* @return
*/
public static bitmap sharpenimageameliorate(bitmap bmp) {
// 拉普拉斯矩阵
int[] laplacian = new int[] { -1, -1, -1, -1, 9, -1, -1, -1, -1 };
int width = bmp.getwidth();
int height = bmp.getheight();
bitmap bitmap = bitmap.createbitmap(width, height,
bitmap.config.rgb_565);
int pixr = 0;
int pixg = 0;
int pixb = 0;
int pixcolor = 0;
int newr = 0;
int newg = 0;
int newb = 0;
int idx = 0;
float alpha = 0.3f;
int[] pixels = new int[width * height];
bmp.getpixels(pixels, 0, width, 0, 0, width, height);
for (int i = 1, length = height - 1; i < length; i++) {
for (int k = 1, len = width - 1; k < len; k++) {
idx = 0;
for (int m = -1; m <= 1; m++) {
for (int n = -1; n <= 1; n++) {
pixcolor = pixels[(i + n) * width + k + m];
pixr = color.red(pixcolor);
pixg = color.green(pixcolor);
pixb = color.blue(pixcolor);
newr = newr + (int) (pixr * laplacian[idx] * alpha);
newg = newg + (int) (pixg * laplacian[idx] * alpha);
newb = newb + (int) (pixb * laplacian[idx] * alpha);
idx++;
}
}
newr = math.min(255, math.max(0, newr));
newg = math.min(255, math.max(0, newg));
newb = math.min(255, math.max(0, newb));
pixels[i * width + k] = color.argb(255, newr, newg, newb);
newr = 0;
newg = 0;
newb = 0;
}
}
bitmap.setpixels(pixels, 0, width, 0, 0, width, height);
return bitmap;
}
5.浮雕
