自动将位图修剪到最小尺寸?

Automatically trim a bitmap to minimum size?(自动将位图修剪到最小尺寸?)
本文介绍了自动将位图修剪到最小尺寸?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

问题描述

假设我有一个 32bpp ARGB 模式的 System.Drawing.Bitmap.这是一个大的位图,但它主要是完全透明的像素,中间有一个相对较小的图像.

Suppose I have a System.Drawing.Bitmap in 32bpp ARGB mode. It's a large bitmap, but it's mostly fully transparent pixels with a relatively small image somewhere in the middle.

检测真实"图像边界的快速算法是什么,这样我就可以剪掉它周围的所有透明像素?

What is a fast algorithm to detect the borders of the "real" image, so I can crop away all the transparent pixels from around it?

或者,.Net 中是否已经有一个函数可以用于此目的?

Alternatively, is there a function already in .Net that I can use for this?

推荐答案

基本思想是检查图像的每个像素点,找到图像的上、左、右、下边界.要有效地执行此操作,请不要使用速度很慢的 GetPixel 方法.改用 LockBits.

The basic idea is to check every pixel of the image to find the top, left, right and bottom bounds of the image. To do this efficiently, don't use the GetPixel method, which is pretty slow. Use LockBits instead.

这是我想出的实现:

static Bitmap TrimBitmap(Bitmap source)
{
    Rectangle srcRect = default(Rectangle);
    BitmapData data = null;
    try
    {
        data = source.LockBits(new Rectangle(0, 0, source.Width, source.Height), ImageLockMode.ReadOnly, PixelFormat.Format32bppArgb);
        byte[] buffer = new byte[data.Height * data.Stride];
        Marshal.Copy(data.Scan0, buffer, 0, buffer.Length);
        int xMin = int.MaxValue;
        int xMax = 0;
        int yMin = int.MaxValue;
        int yMax = 0;
        for (int y = 0; y < data.Height; y++)
        {
            for (int x = 0; x < data.Width; x++)
            {
                byte alpha = buffer[y * data.Stride + 4 * x + 3];
                if (alpha != 0)
                {
                    if (x < xMin) xMin = x;
                    if (x > xMax) xMax = x;
                    if (y < yMin) yMin = y;
                    if (y > yMax) yMax = y;
                }
            }
        }
        if (xMax < xMin || yMax < yMin)
        {
            // Image is empty...
            return null;
        }
        srcRect = Rectangle.FromLTRB(xMin, yMin, xMax, yMax);
    }
    finally
    {
        if (data != null)
            source.UnlockBits(data);
    }

    Bitmap dest = new Bitmap(srcRect.Width, srcRect.Height);
    Rectangle destRect = new Rectangle(0, 0, srcRect.Width, srcRect.Height);
    using (Graphics graphics = Graphics.FromImage(dest))
    {
        graphics.DrawImage(source, destRect, srcRect, GraphicsUnit.Pixel);
    }
    return dest;
}

它可能可以优化,但我不是 GDI+ 专家,所以这是我能做的最好的,无需进一步研究...

It can probably be optimized, but I'm not a GDI+ expert, so it's the best I can do without further research...

实际上,有一种简单的方法可以优化它,即不扫描图像的某些部分:

actually, there's a simple way to optimize it, by not scanning some parts of the image :

  1. 从左到右扫描,直到找到一个不透明的像素;将 (x, y) 存入 (xMin, yMin)
  2. 从上到下扫描,直到找到一个不透明的像素(仅适用于 x >= xMin);将 y 存入 yMin
  3. 从右向左扫描,直到找到一个不透明的像素(仅适用于 y >= yMin);将 x 存入 xMax
  4. 从下往上扫描,直到找到一个不透明的像素(仅适用于 xMin <= x <= xMax);将 y 存入 yMax

<小时>

这是上述方法的实现:


here's an implementation of the approach above:

static Bitmap TrimBitmap(Bitmap source)
{
    Rectangle srcRect = default(Rectangle);
    BitmapData data = null;
    try
    {
        data = source.LockBits(new Rectangle(0, 0, source.Width, source.Height), ImageLockMode.ReadOnly, PixelFormat.Format32bppArgb);
        byte[] buffer = new byte[data.Height * data.Stride];
        Marshal.Copy(data.Scan0, buffer, 0, buffer.Length);

        int xMin = int.MaxValue,
            xMax = int.MinValue,
            yMin = int.MaxValue,
            yMax = int.MinValue;

        bool foundPixel = false;

        // Find xMin
        for (int x = 0; x < data.Width; x++)
        {
            bool stop = false;
            for (int y = 0; y < data.Height; y++)
            {
                byte alpha = buffer[y * data.Stride + 4 * x + 3];
                if (alpha != 0)
                {
                    xMin = x;
                    stop = true;
                    foundPixel = true;
                    break;
                }
            }
            if (stop)
                break;
        }

        // Image is empty...
        if (!foundPixel)
            return null;

        // Find yMin
        for (int y = 0; y < data.Height; y++)
        {
            bool stop = false;
            for (int x = xMin; x < data.Width; x++)
            {
                byte alpha = buffer[y * data.Stride + 4 * x + 3];
                if (alpha != 0)
                {
                    yMin = y;
                    stop = true;
                    break;
                }
            }
            if (stop)
                break;
        }

        // Find xMax
        for (int x = data.Width - 1; x >= xMin; x--)
        {
            bool stop = false;
            for (int y = yMin; y < data.Height; y++)
            {
                byte alpha = buffer[y * data.Stride + 4 * x + 3];
                if (alpha != 0)
                {
                    xMax = x;
                    stop = true;
                    break;
                }
            }
            if (stop)
                break;
        }

        // Find yMax
        for (int y = data.Height - 1; y >= yMin; y--)
        {
            bool stop = false;
            for (int x = xMin; x <= xMax; x++)
            {
                byte alpha = buffer[y * data.Stride + 4 * x + 3];
                if (alpha != 0)
                {
                    yMax = y;
                    stop = true;
                    break;
                }
            }
            if (stop)
                break;
        }

        srcRect = Rectangle.FromLTRB(xMin, yMin, xMax, yMax);
    }
    finally
    {
        if (data != null)
            source.UnlockBits(data);
    }

    Bitmap dest = new Bitmap(srcRect.Width, srcRect.Height);
    Rectangle destRect = new Rectangle(0, 0, srcRect.Width, srcRect.Height);
    using (Graphics graphics = Graphics.FromImage(dest))
    {
        graphics.DrawImage(source, destRect, srcRect, GraphicsUnit.Pixel);
    }
    return dest;
}

当然,如果非透明部分很小,则不会有明显的增益,因为它仍然会扫描大部分像素.但如果它很大,则只会扫描不透明部分周围的矩形.

There won't be a significant gain if the non-transparent part is small of course, since it will still scan most of the pixels. But if it's big, only the rectangles around the non-transparent part will be scanned.

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