private void FillData()
{
var ori = _img.GetPicData();
for (int b = 0; b < _img.BandsCount; b++)
{
var data = _data[b].ConvedData;
for (int i = 0; i < _img.Lines; i++)
{
for (int j = 0; j < _img.Samples; j++)
{
Lapla[b, i, j] = (byte)(data[i, j] + ori[b, i, j]);
}
}
}
}
private void CalcX()
{
// 卷积核书P169
double[,] kernel =
{
{ -1, 0, 1 },
{ -2, 0, 2 },
{ -1, 0, 1 }
};
_dataX = new Conv[_img.BandsCount];
for (int i = 0; i < _img.BandsCount; i++)
{
_dataX[i] = new Conv(_img.GetPicData(i + 1), kernel);
}
}
private void Calc()
{
_data = new Conv[_img.BandsCount];
for (int i = 0; i < _img.BandsCount; i++)
{
_data[i] = new Conv(_img.GetPicData(i + 1), this._kernel);
}
}
/// <summary>
/// 梯度倒数加权-3*3
/// </summary>
public Grad(RsImage r)
{
this._img = r;
this._oriData = r.GetPicData();
GradData = new byte[r.BandsCount, r.Lines, r.Samples];
ScanHoleImg();
}
/// <summary>
/// 梯度倒数加权-3*3
/// </summary>
public Grad(RsImage r)
{
this._img = r;
this._oriData = r.GetPicData();
GradData = new byte[r.BandsCount, r.Lines, r.Samples];
ScanHoleImg();
}
/// <summary>
/// 显示图像-RGB
/// </summary>
/// <param name="ig">图像</param>
public HSI(RsImage ig)
{
InitializeComponent();
InitMousePan();
InitComboBox(ig.BandsCount);
this._img = ig.GetPicData();
}
public ImageStats(RsImage p)
{
_bands = p.BandsCount;
_lines = p.Lines;
_samples = p.Samples;
_picData = p.GetPicData();
CalcStats();
}
/// <summary>
/// 显示图像-RGB
/// </summary>
/// <param name="ig">图像</param>
public KT(RsImage ig)
{
InitializeComponent();
InitMousePan();
InitCombo1();
this._img = ig.GetPicData();
}
public ImageStats(RsImage p)
{
_bands = p.BandsCount;
_lines = p.Lines;
_samples = p.Samples;
_picData = p.GetPicData();
CalcStats();
}
/// <summary>
/// 中值滤波
/// </summary>
/// <param name="r">图像</param>
/// <param name="x">行大小</param>
/// <param name="y">列大小</param>
public Median(RsImage r, int x, int y)
{
this._img = r.GetPicData();
this._sizeX = x;
this._sizeY = y;
this.MedianData = new byte[r.BandsCount, r.Lines, r.Samples];
CheckSize(x, y);
CalcMedian();
}
/// <summary>
/// 中值滤波
/// </summary>
/// <param name="r">图像</param>
/// <param name="x">行大小</param>
/// <param name="y">列大小</param>
public Median(RsImage r, int x, int y)
{
this._img = r.GetPicData();
this._sizeX = x;
this._sizeY = y;
this.MedianData = new byte[r.BandsCount, r.Lines, r.Samples];
CheckSize(x, y);
CalcMedian();
}
public Robert(RsImage img)
{
this._img = img;
this._oriData = img.GetPicData();
this.RobertData = new byte[img.BandsCount, img.Lines, img.Samples];
this._robA = new double[img.BandsCount, img.Lines, img.Samples];
this._robB = new double[img.BandsCount, img.Lines, img.Samples];
ConvForEven();
FillData();
}
public Robert(RsImage img)
{
this._img = img;
this._oriData = img.GetPicData();
this.RobertData = new byte[img.BandsCount, img.Lines, img.Samples];
this._robA = new double[img.BandsCount, img.Lines, img.Samples];
this._robB = new double[img.BandsCount, img.Lines, img.Samples];
ConvForEven();
FillData();
}
/// <summary>
/// 极差纹理
/// </summary>
/// <param name="ig">图像</param>
public RangeFilt(RsImage ig)
{
InitializeComponent();
this._img = ig.GetPicData();
this._final = new byte[_img.GetLength(0)][,];
for (int i = 0; i < this._img.GetLength(0); i++)
{
_final[i] = new RS_Lib.RangeFilt(_img, i).JCWL;
}
InitMousePan();
InitCombo1();
LayerChoice.SelectedIndex = 0;
}
private void CalcMean()
{
// 卷积核书P160
double[,] kernel =
{
{ 0.125, 0.125, 0.125 },
{ 0.125, 0, 0.125 },
{ 0.125, 0.125, 0.125 }
};
_data = new Conv[_img.BandsCount];
for (int i = 0; i < _img.BandsCount; i++)
{
_data[i] = new Conv(_img.GetPicData(i + 1), kernel);
}
}
/// <summary>
/// 构造图像转换器函数
/// </summary>
/// <param name="d">图像数据</param>
/// <param name="t">转换格式(1-bsq,2-bip,3-bil</param>
public PicConvert(RsImage d, int t)
{
this._data = d.GetPicData();
this._convType = t;
this.Convert();
}
/// <summary>
/// 构造图像转换器函数
/// </summary>
/// <param name="d">图像数据</param>
/// <param name="t">转换格式(1-bsq,2-bip,3-bil</param>
public PicConvert(RsImage d, int t)
{
this._data = d.GetPicData();
this._convType = t;
this.Convert();
}
