ios - 快速将图像转换为二进制

Question

我想将图像转换为二进制黑白图像，此时我正在使用普通嵌套循环遍历像素(存储在 UnsafeMutableBufferPointer 中)，将每个 RGB 与平均值进行比较并将其设置为黑色或白色。

这看起来真的很慢，我确信有一种内置的方式可以使用 gpu 或经过很好的优化。如果您可以提供代码示例或链接，那就太好了。

for var y in 0..<height {
    for var x in 0..<width{
        //Pixel is small class i made for 8 bit access and comparison
        if (Buffer[x+y*width]  < AVRRGB) {
            Buffer[x+y*width] = Pixel(RGB: 0x000000FF)
        } else{
            Buffer[x+y*width] = Pixel(RGB: 0xFFFFFFFF)
        }
    }
}

Answer 1

一些观察:

1. 确保您在发布版本(或关闭优化)的设备上进行测试。仅此一项就使它更快。在 iPhone 7+ 上，它将 1920 x 1080 像素彩色图像转换为灰度图像的时间从 1.7 秒减少到不到 0.1 秒。

2. 您可能希望使用 DispatchQueue.concurrentPerform 并发处理像素。在我的 iPhone 7+ 上，速度大约是原来的两倍。

根据我的经验，Core Image 过滤器并没有快多少，但如果您需要更快，可以考虑使用 vImage 或 Metal。但是除非您要处理非常大的图像，否则使用优化的(可能并发的)简单 Swift 代码的响应时间可能就足够了。

一个不相关的观察:

1. 另外，我不确定您的黑白转换是如何进行的，但通常您会想要计算 relative luminance颜色像素(例如 0.2126 * 红色 + 0.7152 * 绿色 + 0.0722 * 蓝色)。当然，当将彩色图像转换为灰度图像时，您会执行类似的操作以获得更接近人眼所见内容的图像，如果转换为黑白图像，我个人也会执行类似的操作。

---

仅供引用，我的 Swift 3/4 颜色到灰度例程如下所示:

func blackAndWhite(image: UIImage, completion: @escaping (UIImage?) -> Void) {
    DispatchQueue.global(qos: .userInitiated).async {
        // get information about image

        let imageref = image.cgImage!
        let width = imageref.width
        let height = imageref.height

        // create new bitmap context

        let bitsPerComponent = 8
        let bytesPerPixel = 4
        let bytesPerRow = width * bytesPerPixel
        let colorSpace = CGColorSpaceCreateDeviceRGB()
        let bitmapInfo = Pixel.bitmapInfo
        let context = CGContext(data: nil, width: width, height: height, bitsPerComponent: bitsPerComponent, bytesPerRow: bytesPerRow, space: colorSpace, bitmapInfo: bitmapInfo)!

        // draw image to context

        let rect = CGRect(x: 0, y: 0, width: CGFloat(width), height: CGFloat(height))
        context.draw(imageref, in: rect)

        // manipulate binary data

        guard let buffer = context.data else {
            print("unable to get context data")
            completion(nil)
            return
        }

        let pixels = buffer.bindMemory(to: Pixel.self, capacity: width * height)

        DispatchQueue.concurrentPerform(iterations: height) { row in
            for col in 0 ..< width {
                let offset = Int(row * width + col)

                let red = Float(pixels[offset].red)
                let green = Float(pixels[offset].green)
                let blue = Float(pixels[offset].blue)
                let alpha = pixels[offset].alpha
                let luminance = UInt8(0.2126 * red + 0.7152 * green + 0.0722 * blue)
                pixels[offset] = Pixel(red: luminance, green: luminance, blue: luminance, alpha: alpha)
            }
        }

        // return the image

        let outputImage = context.makeImage()!
        completion(UIImage(cgImage: outputImage, scale: image.scale, orientation: image.imageOrientation))
    }
}

struct Pixel: Equatable {
    private var rgba: UInt32

    var red: UInt8 {
        return UInt8((rgba >> 24) & 255)
    }

    var green: UInt8 {
        return UInt8((rgba >> 16) & 255)
    }

    var blue: UInt8 {
        return UInt8((rgba >> 8) & 255)
    }

    var alpha: UInt8 {
        return UInt8((rgba >> 0) & 255)
    }

    init(red: UInt8, green: UInt8, blue: UInt8, alpha: UInt8) {
        rgba = (UInt32(red) << 24) | (UInt32(green) << 16) | (UInt32(blue) << 8) | (UInt32(alpha) << 0)
    }

    static let bitmapInfo = CGImageAlphaInfo.premultipliedLast.rawValue | CGBitmapInfo.byteOrder32Little.rawValue

    static func ==(lhs: Pixel, rhs: Pixel) -> Bool {
        return lhs.rgba == rhs.rgba
    }
}

显然，如果您想将其转换为绝对黑白，则相应地调整算法，但这说明了并发图像缓冲区操作例程。

---

虽然上面的速度相当快(同样，在优化的发布版本中)，但使用 vImage 甚至更快。以下内容改编自Converting Color Images to Grayscale :

func grayscale(of image: UIImage) -> UIImage? {
    guard var source = sourceBuffer(for: image) else { return nil }

    defer { free(source.data) }

    var destination = destinationBuffer(for: source)

    // Declare the three coefficients that model the eye's sensitivity
    // to color.
    let redCoefficient: Float = 0.2126
    let greenCoefficient: Float = 0.7152
    let blueCoefficient: Float = 0.0722

    // Create a 1D matrix containing the three luma coefficients that
    // specify the color-to-grayscale conversion.
    let divisor: Int32 = 0x1000
    let fDivisor = Float(divisor)

    var coefficients = [
        Int16(redCoefficient * fDivisor),
        Int16(greenCoefficient * fDivisor),
        Int16(blueCoefficient * fDivisor)
    ]

    // Use the matrix of coefficients to compute the scalar luminance by
    // returning the dot product of each RGB pixel and the coefficients
    // matrix.
    let preBias: [Int16] = [0, 0, 0, 0]
    let postBias: Int32 = 0

    let result = vImageMatrixMultiply_ARGB8888ToPlanar8(
        &source,
        &destination,
        &coefficients,
        divisor,
        preBias,
        postBias,
        vImage_Flags(kvImageNoFlags))

    guard result == kvImageNoError else { return nil }

    defer { free(destination.data) }

    // Create a 1-channel, 8-bit grayscale format that's used to
    // generate a displayable image.
    var monoFormat = vImage_CGImageFormat(
        bitsPerComponent: 8,
        bitsPerPixel: 8,
        colorSpace: Unmanaged.passRetained(CGColorSpaceCreateDeviceGray()),
        bitmapInfo: CGBitmapInfo(rawValue: CGImageAlphaInfo.none.rawValue),
        version: 0,
        decode: nil,
        renderingIntent: .defaultIntent)

    // Create a Core Graphics image from the grayscale destination buffer.
    let cgImage = vImageCreateCGImageFromBuffer(&destination,
                                                &monoFormat,
                                                nil,
                                                nil,
                                               vImage_Flags(kvImageNoFlags),
                                               nil)?.takeRetainedValue()
    return cgImage.map { UIImage(cgImage: $0) }
}


func sourceBuffer(for image: UIImage) -> vImage_Buffer? {
    guard let cgImage = image.cgImage else { return nil }

    let bitmapInfo = CGBitmapInfo(rawValue: CGImageAlphaInfo.premultipliedLast.rawValue).union(.byteOrder32Big)

    var format = vImage_CGImageFormat(bitsPerComponent: 8,
                                      bitsPerPixel: 32,
                                      colorSpace: Unmanaged.passRetained(CGColorSpaceCreateDeviceRGB()),
                                      bitmapInfo: bitmapInfo,
                                      version: 0,
                                      decode: nil,
                                      renderingIntent: .defaultIntent)

    var sourceImageBuffer = vImage_Buffer()
    vImageBuffer_InitWithCGImage(&sourceImageBuffer,
                                 &format,
                                 nil,
                                 cgImage,
                                 vImage_Flags(kvImageNoFlags))

    return sourceImageBuffer

func destinationBuffer(for sourceBuffer: vImage_Buffer) -> vImage_Buffer {
    var destinationBuffer = vImage_Buffer()

    vImageBuffer_Init(&destinationBuffer,
                      sourceBuffer.height,
                      sourceBuffer.width,
                      8,
                      vImage_Flags(kvImageNoFlags))

    return destinationBuffer
}