拉普拉斯算子(laplacian)
如果在图像中一个较暗的区域中出现了一个亮点，那么用拉普拉斯运算就会使这个亮点变得更亮。
拉普拉斯变换效果:
- 强调图像中灰度突变
- 降低灰度慢变化的区域
参考文档https://wenku.baidu.com/view/23a4720a6c85ec3a87c2c598.html
拉普拉斯运算模板
0, 1, 0
1, -4, 1
0, 1, 0
当我们的每一个像素点通过拉普拉斯过滤后, 就会呈现边缘化
precision highp float;
varying lowp vec2 varyTextCoord;
uniform sampler2D texMap;
uniform float stepValue;
const highp vec3 W = vec3(0.2125, 0.7154, 0.0721);
// 卷积核大小
const int kernelSize = 9;
//0-0.009
void main()
{
int i;
vec4 sum = vec4(0.0);
float Kernel[kernelSize];
Kernel[6] = 0.0; Kernel[7] = 1.0; Kernel[8] = 0.0;
Kernel[3] = 1.0; Kernel[4] = -4.0; Kernel[5] = 1.0;
Kernel[0] = 0.0; Kernel[1] = 1.0; Kernel[2] = 0.0;
float fStep = stepValue;
vec2 Offset[kernelSize];
Offset[0] = vec2(-fStep,-fStep); Offset[1] = vec2(0.0,-fStep); Offset[2] = vec2(fStep,-fStep);
Offset[3] = vec2(-fStep,0.0); Offset[4] = vec2(0.0,0.0); Offset[5] = vec2(fStep,0.0);
Offset[6] = vec2(-fStep, fStep); Offset[7] = vec2(0.0, fStep); Offset[8] = vec2(fStep, fStep);
for (i = 0; i < kernelSize; i++)
{
vec4 tmp = texture2D(texMap, varyTextCoord.st + Offset[i]);
sum += tmp * Kernel[i];
}
float luminance = dot(sum.rgb, W);
gl_FragColor = vec4(vec3(luminance), 1.0);
}
灰度边缘检测
Sobel
边检测是一种十分经典的图像处理技术，且可在片元着色器中方便地得以实现。边检测处理技:使用两个Sobel过滤器，分别用于处理分量和垂直分量。前述内容已对Sobel过滤器有所提及，垂直Sob过滤器除了旋转90°之外与水平Sobel过滤器相同。水平过滤器和垂直过滤器分别表示为:
-1, -2, -1
0, 0, 0
1, 2, 1
-1, 0, 1
-2, 0, 2
-1, 0, 1
Sobel过滤器比较间隔为一列(或行)的两列数据(或两行数据，取决于过滤器的类型)，若存在边，则颜色值之间彼此接近，过滤器将返回一个较小值。若返回值或数据值较大，则当前处理过程可判断出边的存在。该测试可在原始图像或仅包含亮度值的图像上进行。
precision highp float;
varying lowp vec2 varyTextCoord;
uniform sampler2D texMap;
/距离中心点多元的距离
uniform float stepValue;
//原色和灰度色的混合比例
uniform float ratioValue;
const highp vec3 W = vec3(0.2125, 0.7154, 0.0721);
const int kernelSize = 9;
//0-0.009
void main()
{
int i;
float hSum = 0.0;
float vSum = 0.0;
vec3 irgb = texture2D( texMap, varyTextCoord).rgb;
vec4 color = vec4(0.0);
float hKernel[kernelSize];
hKernel[0] = -1.0; hKernel[1] = -2.0; hKernel[2] = -1.0;
hKernel[3] = 0.0; hKernel[4] = 0.0; hKernel[5] = 0.0;
hKernel[6] = 1.0; hKernel[7] = 2.0; hKernel[8] = 1.0;
float vKernel[kernelSize];
vKernel[0] = -1.0; vKernel[1] = 0.0; vKernel[2] = 1.0;
vKernel[3] = -2.0; vKernel[4] = 0.0; vKernel[5] = 2.0;
vKernel[6] = -1.0; vKernel[7] = 0.0; vKernel[8] = 1.0;
float fStep = stepValue;
vec2 Offset[kernelSize];
Offset[0] = vec2(-fStep,-fStep); Offset[1] = vec2(0.0,-fStep); Offset[2] = vec2(fStep,-fStep);
Offset[3] = vec2(-fStep,0.0); Offset[4] = vec2(0.0,0.0); Offset[5] = vec2(fStep,0.0);
Offset[6] = vec2(-fStep, fStep); Offset[7] = vec2(0.0, fStep); Offset[8] = vec2(fStep, fStep);
//水平soble过滤器
for (i = 0; i < kernelSize; i++)
{
vec4 tmp = texture2D(texMap, varyTextCoord.st + Offset[i]);
hSum += dot(tmp.rgb, W) * hKernel[i];
}
//垂直soble过滤器
for (i = 0; i < kernelSize; i++)
{
vec4 tmp = texture2D(texMap, varyTextCoord.st + Offset[i]);
vSum += dot(tmp.rgb, W) * vKernel[i];
}
float mag = sqrt( hSum*hSum + vSum*vSum);
vec3 target = vec3( mag,mag,mag );
color = vec4( mix( irgb, target, ratioValue), 1.);
gl_FragColor = color;
}
混合函数是为了将边缘的灰度与原色进行混合, 以达到彩色边缘的效果
color = vec4( mix( irgb, target, ratioValue), 1.);
原色灰度插值边缘检测