关于图像处理中的卷积运算，这里有两份简明扼要的介绍：文一，文二。
其中，可能的一种卷积运算代码如下：
- - (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;
- }
方法的参数kernel是卷积运算中的卷积核，下面是几种滤镜的卷积核：
- #pragma mark -
- #pragma mark - Basic Convolutions
-
-
- - (UIImage *)sharpen
- {
-
- 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];
- }
在此基础上，我Google了下Photoshop中对照片进行黑白处理的简单步骤：
- 去色
- 调整对比度
- 高斯模糊
- 浮雕效果
- 边缘检测
- 调整对比度
- 调整亮度
- 反相
我按步骤实现了相应代码：
- return [[[[[[[[originImage desaturate]
- changeContrastByFactor:1.5]
- gaussianBlur:1.3] emboss]
- edgeDetect]
- changeContrastByFactor:1.5]
- changeBrightnessByFactor:1.5]
- invert];
可惜效果有点粗糙，照片仍旧以
上一篇文章中的Andy为例：
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