问题:
当直接使用文件路径加载8位灰度PNG图片为Bitmap时,Bitmap的格式将会是Format32bppArgb,而不是Format8bppIndexed,这对一些判断会有影响,所以需要手动解析PNG的数据来构造Bitmap
步骤
1. 判断文件格式
若对PNG文件格式不是很了解,阅读本文前可以参考PNG的文件格式 PNG文件格式详解
简而言之,PNG文件头有8个固定字节来标识它,他们是
private static byte[] PNG_IDENTIFIER = { 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A };
2. 判断是否为8位灰度图
识别为PNG文件后,需要判断该PNG文件是否为8位的灰度图
在PNG的文件头标识后是PNG文件的第一个数据块IHDR
,它的数据域由13个字节组成
域的名称 | 数据字节数 | 说明 |
---|---|---|
Width | 4 bytes | 图像宽度,以像素为单位 |
Height | 4 bytes | 图像高度,以像素为单位 |
Bit depth | 1 byte | 图像深度:索引彩色图像:1,2,4或8 ;灰度图像:1,2,4,8或16 ;真彩色图像:8或16 |
ColorType | 1 byte | 颜色类型:0:灰度图像, 1,2,4,8或16;2:真彩色图像,8或16;3:索引彩色图像,1,2,4或84:带α通道数据的灰度图像,8或16;6:带α通道数据的真彩色图像,8或16 |
Compression method | 1 byte | 压缩方法(LZ77派生算法) |
Filter method | 1 byte | 滤波器方法 |
Interlace method | 1 byte | 隔行扫描方法:0:非隔行扫描;1: Adam7(由Adam M. Costello开发的7遍隔行扫描方法) |
这里我们看颜色深度以及颜色类型就行
var ihdrData = data[(PNG_IDENTIFIER.Length + 8)..(PNG_IDENTIFIER.Length + 8 + 13)];
var bitDepth = Convert.ToInt32(ihdrData[8]);
var colorType = Convert.ToInt32(ihdrData[9]);
这里的data
是表示PNG文件的byte数组,+8是因为PNG文件的每个数据块的数据域前都有4个字节的数据域长度和4个字节的数据块类型(名称)
3. 获取全部图像数据块
PNG文件的图像数据由一个或多个图像数据块IDAT
构成,并且他们是顺序排列的
这里通过while
循环找到所有的IDAT
块
var compressedSubDats = new List<byte[]>();
var firstDatOffset = FindChunk(data, "IDAT");
var firstDatLength = GetChunkDataLength(data, firstDatOffset);
var firstDat = new byte[firstDatLength];
Array.Copy(data, firstDatOffset + 8, firstDat, 0, firstDatLength);
compressedSubDats.Add(firstDat);
var dataSpan = data.AsSpan().Slice(firstDatOffset + 12 + firstDatLength);
while (Encoding.ASCII.GetString(dataSpan[4..8]) == "IDAT")
{
var datLength = dataSpan.ReadBinaryInt(0, 4);
var dat = new byte[datLength];
dataSpan.Slice(8, datLength).CopyTo(dat);
compressedSubDats.Add(dat);
dataSpan = dataSpan.Slice(12 + datLength);
}
var compressedDatLength = compressedSubDats.Sum(a => a.Length);
var compressedDat = new byte[compressedDatLength].AsSpan();
var index = 0;
for (int i = 0; i < compressedSubDats.Count; i++)
{
var subDat = compressedSubDats[i];
subDat.CopyTo(compressedDat.Slice(index, subDat.Length));
index += subDat.Length;
}
4. 解压DAT数据
上一步获得的DAT数据是由Deflate
算法压缩后的,我们需要将它解压缩,这里使用.NET自带的DeflateStream
进行解压缩
IDAT的数据流以zlib格式存储,结构为
名称 | 长度 |
---|---|
zlib compression method/flags code | 1 byte |
Additional flags/check bits | 1 byte |
Compressed data blocks | n bytes |
Check value | 4 bytes |
解压缩时去掉前2个字节
var deCompressedDat = MicrosoftDecompress(compressedDat.ToArray()[2..]).AsSpan();
public static byte[] MicrosoftDecompress(byte[] data)
{
MemoryStream compressed = new MemoryStream(data);
MemoryStream decompressed = new MemoryStream();
DeflateStream deflateStream = new DeflateStream(compressed, CompressionMode.Decompress);
deflateStream.CopyTo(decompressed);
byte[] result = decompressed.ToArray();
return result;
}
5. 重建原始数据
PNG的IDAT
数据流在压缩前会通过过滤算法将原始数据进行过滤来提高压缩率,这里需要将过滤后的数据进行重建
有关过滤和重建可以参考W3组织的文档
这里定义了一个类来辅助重建
public class PngFilterByte
{
public PngFilterByte(int filterType, int row, int col)
{
FilterType = filterType;
Row = row;
Column = col;
}
public int Row { get; set; }
public int Column { get; set; }
public int FilterType { get; set; }
public PngFilterByte C { get; set; }
public PngFilterByte B { get; set; }
public PngFilterByte A { get; set; }
public int X { get; set; }
private bool _isTop;
public bool IsTop
{
get => _isTop;
init
{
_isTop = value;
if (!_isTop) return;
B = Zero;
}
}
private bool _isLeft;
public bool IsLeft
{
get => _isLeft;
init
{
_isLeft = value;
if (!_isLeft) return;
A = Zero;
}
}
public int _filt;
public int Filt
{
get => IsFiltered ? _filt : DoFilter();
init
{
_filt = value;
}
}
public bool IsFiltered { get; set; } = false;
public int DoFilter()
{
_filt = FilterType switch
{
0 => X,
1 => X - A.X,
2 => X - B.X,
3 => X - (int)Math.Floor((A.X + B.X) / 2.0M),
4 => X - Paeth(A.X, B.X, C.X),
_ => X
};
if (_filt > 255) _filt %= 256;
IsFiltered = true;
return _filt;
}
private int _recon;
public int Recon
{
get => IsReconstructed ? _recon : DoReconstruction();
init
{
_filt = value;
}
}
public bool IsReconstructed { get; set; } = false;
public int DoReconstruction()
{
_recon = FilterType switch
{
0 => Filt,
1 => Filt + A.Recon,
2 => Filt + B.Recon,
3 => Filt + (int)Math.Floor((A.Recon + B.Recon) / 2.0M),
4 => Filt + Paeth(A.Recon, B.Recon, C.Recon),
_ => Filt
};
if (_recon > 255) _recon %= 256;
X = _recon;
IsReconstructed = true;
return _recon;
}
private int Paeth(int a, int b, int c)
{
var p = a + b - c;
var pa = Math.Abs(p - a);
var pb = Math.Abs(p - b);
var pc = Math.Abs(p - c);
if (pa <= pb && pa <= pc)
{
return a;
}
else if (pb <= pc)
{
return b;
}
else
{
return c;
}
}
public static PngFilterByte Zero = new PngFilterByte(0, -1, -1)
{
IsFiltered = true,
IsReconstructed = true,
X = 0,
Filt = 0,
Recon = 0
};
}
下面获取重建的数据
首先从IHDR
获取宽高
var width = ihdrData.ReadBinaryInt(0, 4);
var height = ihdrData.ReadBinaryInt(4, 4);
按行处理
var filtRowDic = new Dictionary<int, byte[]>();
for (int i = 0; i < height; i++)
{
var rowData = deCompressedDat.Slice(i * (width + 1), (width + 1));
filtRowDic.Add(i, rowData.ToArray());
}
var rowColDic = new Dictionary<(int, int), PngFilterByte>();
for (int i = 0; i < height; i++)
{
var row = filtRowDic[i];
var filterType = row[0];
for (int j = 1; j <= width; j++)
{
var bt = new PngFilterByte(filterType, i, j - 1)
{
Filt = Convert.ToInt32(row[j]),
IsFiltered = true,
IsTop = i == 0,
IsLeft = j == 1
};
if (bt.IsTop && bt.IsLeft)
{
bt.C=PngFilterByte.Zero;
}
if (!bt.IsTop)
{
bt.B = rowColDic[(bt.Row - 1, bt.Column)];
}
if (!bt.IsLeft)
{
bt.A = rowColDic[(bt.Row, bt.Column - 1)];
}
rowColDic.Add((bt.Row, bt.Column), bt);
}
}
var realImageData = new byte[rowColDic.Count];
foreach (var bt in rowColDic.Values)
{
realImageData[bt.Row * width + bt.Column] = Convert.ToByte(bt.Recon);
}
6. 最后构建灰度Bitmap并赋予数据
using var bitmap = new Bitmap(width, height, PixelFormat.Format8bppIndexed);
ColorPalette cp = bitmap.Palette;
for (int i = 0; i < 256; i++)
{
cp.Entries[i] = Color.FromArgb(i, i, i);
}
bitmap.Palette = cp;
var bmpData = bitmap.LockBits(new Rectangle(0, 0, width, height), ImageLockMode.ReadWrite, PixelFormat.Format8bppIndexed);
Marshal.Copy(realImageData, 0, bmpData.Scan0, realImageData.Length);
bitmap.UnlockBits(bmpData);
return bitmap;
完整代码
Github Gist
参考:文章来源:https://www.toymoban.com/news/detail-711815.html
1. PNG文件格式详解
2. Png的数据解析
3. How to read 8-bit PNG image as 8-bit PNG image only?
4. Portable Network Graphics (PNG) Specification (Second Edition)文章来源地址https://www.toymoban.com/news/detail-711815.html
到了这里,关于C# 手动解析灰度PNG图片为Bitmap的文章就介绍完了。如果您还想了解更多内容,请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章,希望大家以后多多支持TOY模板网!