问题描述
我有 Basler acA3800 USB 相机.
IGrabResult grabResult = camera.StreamGrabber.RetrieveResult(5000, TimeoutHandling.ThrowException);//图片抓取成功?如果(grabResult.GrabSucceeded){byte[] buffer = grabResult.PixelData as byte[];ImageWindow.DisplayImage(0, grabResult);pictureBox1.Image = ImageFromRawBgraArray(buffer,3840,2748,PixelFormat.Format8bppIndexed);MessageBox.Show(grabResult.PixelTypeValue.ToString());}
此代码部分显示图像自身窗口.
我有捕获图像的像素数据.原始图像很好,但是当我将其转换为图像时,它已损坏.这是我的转换函数.
public Image ImageFromRawBgraArray(byte[] arr, int width, int height, PixelFormat pixelFormat){var output = new Bitmap(width, height, pixelFormat);var rect = new Rectangle(0, 0, width, height);var bmpData = output.LockBits(rect, ImageLockMode.ReadWrite, output.PixelFormat);//逐行复制var arrRowLength = 宽度 * Image.GetPixelFormatSize(output.PixelFormat)/8;var ptr = bmpData.Scan0;for (var i = 0; i <高度; i++){Marshal.Copy(arr, i * arrRowLength, ptr, arrRowLength);ptr += bmpData.Stride;}输出.UnlockBits(bmpData);返回输出;}
我认为这与像素类型有关.我选择了 PixelFormat.Format8bppIndexed 的像素格式.其他的不工作.
MessageBox.Show(grabResult.PixelTypeValue.ToString());
这个消息框给了我像素类型.上面写着BayerBG8".这是什么意思?我应该怎么做才能获得清晰的图像?
你得到的奇怪颜色是因为 Format8bppIndexed
是调色板,你从不编辑调色板,这意味着它保留了默认生成的 Windows调色板.但在您的情况下,此调色板无关紧要,因为图像 不是 8 位索引格式;需要对其进行处理以将其转换为 RGB.
BayerBG8 的快速 google 找到了我介绍这些内容的一般处理方式,但 .
请注意,上面的去马赛克方法非常基本,并且会显示 许多预期的工件.有更先进的方法可以分析数据并根据图像的拍摄方式获得更准确的结果,但您可能需要进行大量研究才能弄清楚所有这些并自己实施.
这是我做的一个小测试,从 我在网上找到的经过拜耳过滤的图像(第一张图像),我将其转换为 8 位数组(此处显示为灰度;第二张图像).如您所见,我自己的去马赛克(第三张图片)远不如他们从中得到的校正版本(第四张图片)准确,而且,值得注意的是,它小了一个像素,因此显示为白色边框.
(请注意,与上面的示例不同,此图像以绿色像素开头,这意味着必须调整解码参数)
I have Basler acA3800 USB camera.
IGrabResult grabResult = camera.StreamGrabber.RetrieveResult(5000, TimeoutHandling.ThrowException);
// Image grabbed successfully?
if (grabResult.GrabSucceeded)
{
byte[] buffer = grabResult.PixelData as byte[];
ImageWindow.DisplayImage(0, grabResult);
pictureBox1.Image = ImageFromRawBgraArray(buffer,3840,2748,PixelFormat.Format8bppIndexed);
MessageBox.Show(grabResult.PixelTypeValue.ToString());
}
This code section shows image self window.
I have pixel data of captured image. Original image is good but when I convert it to Image, it corrupt. And here is my conversion function.
public Image ImageFromRawBgraArray(byte[] arr, int width, int height, PixelFormat pixelFormat)
{
var output = new Bitmap(width, height, pixelFormat);
var rect = new Rectangle(0, 0, width, height);
var bmpData = output.LockBits(rect, ImageLockMode.ReadWrite, output.PixelFormat);
// Row-by-row copy
var arrRowLength = width * Image.GetPixelFormatSize(output.PixelFormat) / 8;
var ptr = bmpData.Scan0;
for (var i = 0; i < height; i++)
{
Marshal.Copy(arr, i * arrRowLength, ptr, arrRowLength);
ptr += bmpData.Stride;
}
output.UnlockBits(bmpData);
return output;
}
I think it is about pixel type. I have selected pixel format of PixelFormat.Format8bppIndexed. The others is not working.
MessageBox.Show(grabResult.PixelTypeValue.ToString());
This messagebox gives me the pixeltype. and it says "BayerBG8". What does it mean? What should I do to get clear image?
The odd colours you are getting are because Format8bppIndexed
is paletted, and you never edit the palette, meaning it retains the default generated Windows palette. But in your case, this palette is irrelevant, because the image is not an 8-bit indexed format; it needs to be processed to convert it to RGB.
A quick google for BayerBG8 got me this page. The Bayer section there shows it's a rather peculiar transformation to use specifically patterned indices on the image as R, G and B.
Wikipedia has a whole article on how this stuff is generally processed, but this YouTube video shows the basics:
Note that this is a sliding window; for the first pixel, the colours are
R G G B
but for the second pixel, they'll be
G R B G
and for one row down, the first one will use
G B R G
You'll end up with an image that is one pixel less wide and high than the given dimensions, since the last pixel on each row and all pixels on the last row won't have the neighbouring data needed to get their full pixel data. There are apparently more advanced algorithms to get around that, but for this method I'll just go over the basic sliding window method.
public static Byte[] BayerToRgb(Byte[] arr, ref Int32 width, ref Int32 height, ref Int32 stride, Boolean greenFirst, Boolean blueRowFirst)
{
Int32 actualWidth = width - 1;
Int32 actualHeight = height - 1;
Int32 actualStride = actualWidth*3;
Byte[] result = new Byte[actualStride*actualHeight];
for (Int32 y = 0; y < actualHeight; y++)
{
Int32 curPtr = y*stride;
Int32 resPtr = y*actualStride;
Boolean blueRow = y % 2 == (blueRowFirst ? 0 : 1);
for (Int32 x = 0; x < actualWidth; x++)
{
// Get correct colour components from sliding window
Boolean isGreen = (x + y) % 2 == (greenFirst ? 0 : 1);
Byte cornerCol1 = isGreen ? arr[curPtr + 1] : arr[curPtr];
Byte cornerCol2 = isGreen ? arr[curPtr + stride] : arr[curPtr + stride + 1];
Byte greenCol1 = isGreen ? arr[curPtr] : arr[curPtr + 1];
Byte greenCol2 = isGreen ? arr[curPtr + stride + 1] : arr[curPtr + stride];
Byte blueCol = blueRow ? cornerCol1 : cornerCol2;
Byte redCol = blueRow ? cornerCol2 : cornerCol1;
// 24bpp RGB is saved as [B, G, R].
// Blue
result[resPtr + 0] = blueCol;
// Green
result[resPtr + 1] = (Byte) ((greenCol1 + greenCol2)/2);
// Red
result[resPtr + 2] = redCol;
curPtr++;
resPtr+=3;
}
}
height = actualHeight;
width = actualWidth;
stride = actualStride;
return result;
}
The parameters greenFirst
and blueRowFirst
indicate whether green is the first encountered pixel on the image, and whether the blue pixels are on the first or second row. For your "BG" format, both of these should be false.
From the result of this, with the adjusted width, height and stride, you can convert that to a new image using the method you already used, but with Format24bppRgb
as pixel format.
Personally I use a somewhat more advanced method that takes the input stride into account and can handle indexed content. If you're interested, that method can be found here.
Note that the demosaicing method above is very basic, and will show many of the expected artifacts. There are more advanced methods out there to analyse the data and get more accurate results based on how the image was taken, but it'll probably cost you quite some research to figure all that out and implement it yourself.
Here's a little test I did, starting from a Bayer-filtered image I found online (first image) which I converted to an 8-bit array (shown here as grayscale; second image). As you can see, my own demosaicing (third image) is far less accurate than the corrected version they got out of it (fourth image), and, notably, is one pixel smaller and thus shows a white border.
(Note that, unlike the examples above, this image starts with a green pixel, meaning the parameters to decode it had to be adjusted)
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