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iOS中的圖像處理（二）——卷積運算
關於圖像處理中的卷積運算，這裏有兩份簡明扼要的介紹：文一，文二。
其中，可能的一種卷積運算代碼如下：
- (UIImage*)applyConvolution:(NSArray*)kernel
{
CGImageRef inImage = self.CGImage;
CFDataRef m_DataRef = CGDataProviderCopyData(CGImageGetDataProvider(inImage));
CFDataRef m_OutDataRef = CGDataProviderCopyData(CGImageGetDataProvider(inImage));
UInt8 * m_PixelBuf = (UInt8 *) CFDataGetBytePtr(m_DataRef);
UInt8 * m_OutPixelBuf = (UInt8 *) CFDataGetBytePtr(m_OutDataRef);
int h = CGImageGetHeight(inImage);
int w = CGImageGetWidth(inImage);
int kh = [kernel count] / 2;
int kw = [[kernel objectAtIndex:0] count] / 2;
int i = 0, j = 0, n = 0, m = 0;
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
int outIndex = (i*w*4) + (j*4);
double r = 0, g = 0, b = 0;
for (n = -kh; n <= kh; n++) {
for (m = -kw; m <= kw; m++) {
if (i + n >= 0 && i + n < h) {
if (j + m >= 0 && j + m < w) {
double f = [[[kernel objectAtIndex:(n + kh)] objectAtIndex:(m + kw)] doubleValue];
if (f == 0) {continue;}
int inIndex = ((i+n)*w*4) + ((j+m)*4);
r += m_PixelBuf[inIndex] * f;
g += m_PixelBuf[inIndex + 1] * f;
b += m_PixelBuf[inIndex + 2] * f;
}
}
}
}
m_OutPixelBuf[outIndex] = SAFECOLOR((int)r);
m_OutPixelBuf[outIndex + 1] = SAFECOLOR((int)g);
m_OutPixelBuf[outIndex + 2] = SAFECOLOR((int)b);
m_OutPixelBuf[outIndex + 3] = 255;
}
}
CGContextRef ctx = CGBitmapContextCreate(m_OutPixelBuf,
CGImageGetWidth(inImage),
CGImageGetHeight(inImage),
CGImageGetBitsPerComponent(inImage),
CGImageGetBytesPerRow(inImage),
CGImageGetColorSpace(inImage),
CGImageGetBitmapInfo(inImage)
);
CGImageRef imageRef = CGBitmapContextCreateImage(ctx);
CGContextRelease(ctx);
UIImage *finalImage = [UIImage imageWithCGImage:imageRef];
CGImageRelease(imageRef);
CFRelease(m_DataRef);
CFRelease(m_OutDataRef);
return finalImage;
}
方法的參數kernel是卷積運算中的卷積核，下麵是幾種濾鏡的卷積核：
#pragma mark -
#pragma mark - Basic Convolutions
/* Reference :
* https://docs.gimp.org/en/plug-in-convmatrix.html
*/
- (UIImage *)sharpen
{
// double dKernel[5][5] = {
// {0, 0.0, -1.0, 0.0, 0},
// {0, -1.0, 5.0, -1.0, 0},
// {0, 0.0, -1.0, 0.0, 0}
// };
double dKernel[5][5] = {
{0, 0.0, -0.2, 0.0, 0},
{0, -0.2, 1.8, -0.2, 0},
{0, 0.0, -0.2, 0.0, 0}
};
NSMutableArray *kernel = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int i = 0; i < 5; i++) {
NSMutableArray *row = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int j = 0; j < 5; j++) {
[row addObject:[NSNumber numberWithDouble:dKernel[i][j]]];
}
[kernel addObject:row];
}
return [self applyConvolution:kernel];
}
- (UIImage *)edgeEnhance
{
double dKernel[5][5] = {
{0, 0.0, 0.0, 0.0, 0},
{0, -1.0, 1.0, 0.0, 0},
{0, 0.0, 0.0, 0.0, 0}
};
NSMutableArray *kernel = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int i = 0; i < 5; i++) {
NSMutableArray *row = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int j = 0; j < 5; j++) {
[row addObject:[NSNumber numberWithDouble:dKernel[i][j]]];
}
[kernel addObject:row];
}
return [self applyConvolution:kernel];
}
- (UIImage *)edgeDetect
{
double dKernel[5][5] = {
{0, 0.0, 1.0, 0.0, 0},
{0, 1.0, -4.0, 1.0, 0},
{0, 0.0, 1.0, 0.0, 0}
};
NSMutableArray *kernel = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int i = 0; i < 5; i++) {
NSMutableArray *row = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int j = 0; j < 5; j++) {
[row addObject:[NSNumber numberWithDouble:dKernel[i][j]]];
}
[kernel addObject:row];
}
return [self applyConvolution:kernel];
}
- (UIImage *)emboss
{
double dKernel[5][5] = {
{0, -2.0, -1.0, 0.0, 0},
{0, -1.0, 1.0, 1.0, 0},
{0, 0.0, 1.0, 2.0, 0}
};
NSMutableArray *kernel = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int i = 0; i < 5; i++) {
NSMutableArray *row = [[[NSMutableArray alloc] initWithCapacity:5] autorelease];
for (int j = 0; j < 5; j++) {
[row addObject:[NSNumber numberWithDouble:dKernel[i][j]]];
}
[kernel addObject:row];
}
return [self applyConvolution:kernel];
}
在此基礎上，我Google了下Photoshop中對照片進行黑白處理的簡單步驟：
- 去色
- 調整對比度
- 高斯模煳
- 浮雕效果
- 邊緣檢測
- 調整對比度
- 調整亮度
- 反相
我按步驟實現了相應代碼：
return [[[[[[[[originImage desaturate]
changeContrastByFactor:1.5]
gaussianBlur:1.3] emboss]
edgeDetect]
changeContrastByFactor:1.5]
changeBrightnessByFactor:1.5]
invert];
可惜效果有點粗糙，照片仍舊以上一篇文章中的Andy為例：
最後更新：2017-04-02 16:48:10