基于C语言的最大值滤波

最新推荐文章于 2024-01-25 08:00:00 发布

原创最新推荐文章于 2024-01-25 08:00:00 发布 · 394 阅读

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CC 4.0 BY-SA版权

本文介绍了一种二维图像最大值滤波算法的实现细节，包括图像的扩展处理、行方向和列方向最大值的查找，以及最终滤波结果的生成。该算法通过寻找每个像素周围特定邻域内的最大值来增强图像特征。

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void MaxFilter(unsigned int *src, unsigned int *dst, int width, int height)
{
	assert(src != NULL);
	assert(dst != NULL);
	assert(width >= 0);
	assert(height >= 0);

	memset(expandDwtImageBuff, 0, EXPAND_IMAGE_SIZE * sizeof(unsigned int));
	memset(maxCols, 0, EXPAND_IMAGE_SIZE * sizeof(unsigned int));
	memset(maxRows, 0, EXPAND_IMAGE_SIZE * sizeof(unsigned int));
	int expWidth = width + 2 * EXPAND_SIZE;
	int expHeight = height + 2 * EXPAND_SIZE;

	// 对输入图像进行扩展
	for (int y = 0; y < height; y++)
	{
		for (int x = 0; x < width; x++)
			expandDwtImageBuff[(y + EXPAND_SIZE) * expWidth + x + EXPAND_SIZE] = src[y * width + x];
	}

	// 找行方向的最大值（每一行41*1邻域的最大值）
	unsigned int maxColValue = 0;	// 最大值
	Point maxColPos = { 0, 0 };		// 最大值坐标
	const int localDwtLen = 2 * EXPAND_SIZE + 1;

	for (int y = EXPAND_SIZE; y < height + EXPAND_SIZE; y++)
	{
		int starty = y;
		int endy = starty;
		for (int x = EXPAND_SIZE; x < width + EXPAND_SIZE; x++)
		{
			if (expandDwtImageBuff[y * expWidth + x] > 0)
			{
				int startx = x - EXPAND_SIZE;
				int endx = x + EXPAND_SIZE;

				// 最大值求解
				if (x == EXPAND_SIZE || maxColPos.x < startx)
				{
					GetMaxLocation(expandDwtImageBuff + starty * expWidth + startx, localDwtLen, &maxColValue, &maxColPos.x);
					maxColPos.x += startx;
					maxColPos.y += starty;
					maxCols[y * expWidth + x] = maxColValue;
				}
				else
				{

					// 在移入的范围内，比较最大值和移入值
					int newValue = expandDwtImageBuff[y * expWidth + endx];
					if (newValue >= maxColValue)
					{
						maxColValue = newValue;
						maxColPos.x = endx;
						maxColPos.y = y;
					}
					maxCols[y * expWidth + x] = maxColValue;
				}
			}
		}
		maxColPos.x = 0;
		maxColPos.y = 0;
	}

	// 找列方向的最大值（maxCols中每一列1*41邻域的最大值）
	unsigned int maxRowValue = 0;
	Point maxRowPos = { 0, 0 };
	unsigned int localDwtBuff[2 * EXPAND_SIZE + 1] = { 0 };

	for (int x = EXPAND_SIZE; x < width + EXPAND_SIZE; x++)
	{
		int startx = x;
		int endx = startx;
		for (int y = EXPAND_SIZE; y < height + EXPAND_SIZE; y++)
		{
			int starty = y - EXPAND_SIZE;
			int endy = y + EXPAND_SIZE;

			// 最大值求解
			if (y == EXPAND_SIZE || maxRowPos.y < starty)
			{
				for (int i = 0; i < localDwtLen; i++)
					localDwtBuff[i] = maxCols[(starty + i) * expWidth + startx];
				GetMaxLocation(localDwtBuff, localDwtLen, &maxRowValue, &maxRowPos.y);
				maxRowPos.y += starty;
				maxRows[y * expWidth + x] = maxRowValue;
			}
			else
			{
				// 在移入的范围内，比较最大值和移入值
				// 移入值为1*41矩形区域中最后一个值
				int newValue = maxCols[endy * expWidth + x];
				if (newValue >= maxRowValue)
				{
					maxRowValue = newValue;
					maxRowPos.y = endy;
				}
				maxRows[y * expWidth + x] = maxRowValue;
			}

			if (expandDwtImageBuff[y * expWidth + x] == 0)
				maxRows[y * expWidth + x] = 0;
		}
	}

	// 切掉扩展出来的边缘
	for (int y = 0; y < height; y++)
	{
		for (int x = 0; x < width; x++)
			dst[y * width + x] = maxRows[(y + EXPAND_SIZE) * expWidth + x + EXPAND_SIZE];
	}
}