public void TestGenerateDCTReverseBlock()
{
double[,] block = new double[4, 4]
{
{ 242.7500, 48.4317, -9.7500, 23.5052 },
{ -12.6428, -54.0659, 7.4278, 22.7950 },
{ -6.2500, 10.7158, -19.7500, -38.8046 },
{ 40.6852, -38.7050, -11.4653, -45.9341 }
};
var matrix = DCTCompression.GenerateDCTReverseBlock(block);
var shouldBe = new int[4, 4]
{
{ 42, 66, 68, 66 },
{ 92, 4, 76, 17 },
{ 79, 85, 74, 71 },
{ 96, 93, 39, 3 }
};
for (int i = 0; i < 4; i++)
{
for (int k = 0; k < 4; k++)
{
Assert.Equal(shouldBe[i, k], matrix[i, k]);
}
}
}
public void TestGetDCTImage()
{
var image = ImageFile.LoadBmpImage("..\\..\\..\\TestImages\\lenna_gray.bmp");
BmpImage dctImage = new DCTCompression(image, 15).GetDCTImage();
ImageFile.SaveBmpImage(dctImage, "..\\..\\..\\TestImages\\lenna_dct_modified.bmp");
}
public void TestGetDCTReverseImageWithCompression()
{
var image = ImageFile.LoadBmpImage("..\\..\\..\\TestImages\\lenna_gray.bmp");
var dct = new DCTCompression(image, 15);
BmpImage dctImage = dct.GetDCTImage();
ImageFile.SaveBmpImage(dctImage, "..\\..\\..\\TestImages\\lenna_dct_comp_modified.bmp");
BmpImage reverseImage = dct.GetDCTReverseImage(8.0);
ImageFile.SaveBmpImage(reverseImage, "..\\..\\..\\TestImages\\lenna_dct_reverse_comp_modified.bmp");
}
private static void ModuleThree(BmpImage image)
{
/*
* 图像压缩模块
* 1.无损预测编码+符号编码
* 2.均匀量化
* 3.DCT变换及DCT反变换
*/
int photoFormat = CheckPhoto(image);
if (photoFormat == 1)
{
System.Console.WriteLine("\n检测图片为8bit灰度图像");
System.Console.WriteLine("可选择的压缩模式：\n1.无损预测编码\n2.均匀量化\n3.DCT变换及DCT反变换\n0.返回");
bool inputNum = false;
do
{
try
{
int num = Convert.ToInt32(System.Console.ReadLine());
if (num < 4 && num > -1)
{
inputNum = true;
//1.无损预测编码
if (num == 1)
{
System.Console.WriteLine("\n输如文件保存的路径：");
string CompressPath = System.Console.ReadLine();
string savedFilePath = Path.GetDirectoryName(CompressPath);
string fileName = Path.GetFileNameWithoutExtension(CompressPath);
LinearPredictor lp = new LinearPredictor(image, savedFilePath, fileName);
lp.predicate();
//system.console.writeline("{0},{1}", savedfilepath, filename);
System.Console.WriteLine("***************保存中***************");
System.Console.WriteLine("压缩文件已保存至{0}\n", CompressPath);
System.Console.WriteLine("完成无损预测编码！");
}
//2.均匀量化
else if (num == 2)
{
System.Console.WriteLine("\n压缩比（输如0为IGS量化）：");
double CompressRatio = Convert.ToDouble(System.Console.ReadLine());
if (CompressRatio == 0)
{
UniformQuantizing igs = new UniformQuantizing(image);
image = igs.InverseUniformQuantizaing();
}
else
{
UniformQuantizing uq = new UniformQuantizing(image, CompressRatio);
image = uq.InverseUniformQuantizaing();
}
System.Console.WriteLine("完成均匀量化！");
}
//3.DCT变换及DCT反变换
else if (num == 3)
{
System.Console.WriteLine("\n设置分块大小：");
int blockSize = Convert.ToInt32(System.Console.ReadLine());
var dct = new DCTCompression(image, blockSize);
image = dct.GetDCTImage();
//DCT反变换
BmpImage reverseImage = dct.GetDCTReverseImage(1.0);
//即将50%的高频系数用0代替 DCT反变换
BmpImage reverseHalfImage = dct.GetDCTReverseImage(2.0);
System.Console.WriteLine("\n把DCT反变换的结果存储至：");
string reverseImagePath = System.Console.ReadLine();
ImageFile.SaveBmpImage(reverseImage, @reverseImagePath);
System.Console.WriteLine("显示图片？(1 or 2）");
int display1 = Convert.ToInt32(System.Console.ReadLine());
if (display1 == 1)
{
showPhoto(reverseImagePath);
}
System.Console.WriteLine("把DCT反变换(50%)的结果存储至：");
string reverseHalfImagePath = System.Console.ReadLine();
ImageFile.SaveBmpImage(reverseHalfImage, @reverseHalfImagePath);
System.Console.WriteLine("显示图片？(1 or 2）");
int display2 = Convert.ToInt32(System.Console.ReadLine());
if (display2 == 1)
{
showPhoto(reverseHalfImagePath);
}
System.Console.WriteLine("完成DCT变换及反变换！");
}
else
{
;
}
}
else
{
System.Console.Write("输入错误请重新输入:");
}
}
catch (OverflowException)
{
System.Console.WriteLine("err:转化的不是一个int型数据");
}
catch (FormatException)
{
System.Console.WriteLine("err:格式错误");
}
catch (ArgumentNullException)
{
System.Console.WriteLine("err:null");
}
} while (inputNum == false);
}
else
{
System.Console.Write("\n图片形式不支持图像压缩哟~\n");
}
}
