在GDI中向图像添加下拉阴影的有效方法是什么?
现在我从我的形象开始:

我使用ImageAttributes和ColorMatrix将图像的alpha掩码绘制为新图像:
colorMatrix = (
( 0, 0, 0, 0, 0),
( 0, 0, 0, 0, 0),
( 0, 0, 0, 0, 0),
(-1, -1, -1, 1, 0),
( 1, 1, 1, 0, 1)
);

然后我应用了一个高斯模糊卷积核,并稍微抵消了它:

然后我把我原来的形象画在上面:

问题是它太慢了,用掉影生成图像需要170 is左右,第2节没有掉影(慢70倍):
带下拉阴影的171,332 µs
2,457us:
当用户(如me)滚动一个项目列表时,额外的169 me延迟是非常明显的。
您可以忽略下面的代码,它不会给问题添加任何内容,也不会增加答案:
class function TImageEffects.GenerateDropShadow(image: TGPImage;
const radius: Single; const OffsetX, OffsetY: Single; const Opacity: Single): TGPBitmap;
var
width, height: Integer;
alphaMask: TGPBitmap;
shadow: TGPBitmap;
graphics: TGPGraphics;
imageAttributes: TGPImageAttributes;
cm: TColorMatrix;
begin
{
We generate a drop shadow by first getting the alpha mask. This will be a black
sillouette on a transparent background. We then blur the black "shadow" by the amounts
given.
We then draw the original image on top of it's own shadow.
}
{
http://msdn.microsoft.com/en-us/library/aa511280.aspx
Windows Vista User Experience -> Guidelines -> Aesthetics -> Icons
Basic Flat Icon Shadow Ranges
Flat icons
Flat icons are generally used for file icons and flat real-world objects,
such as a document or a piece of paper.
Flat icon lighting comes from the upper-left at 130 degrees.
Smaller icons (for example, 16x16 and 32x32) are simplified for readability.
However, if they contain a reflection within the icon (often simplified),
they may have a tight drop shadow. The drop shadow ranges in opacity from
30-50 percent.
Layer effects can be used for flat icons, but should be compared with other
flat icons. The shadows for objects will vary somewhat, according to what
looks best and is most consistent within the size set and with the other
icons in Windows Vista. On some occasions, it may even be necessary to
modify the shadows. This will especially be true when objects are laid over
others.
A subtle range of colors may be used to achieve desired outcome. Shadows help
objects sit in space. Color impacts the perceived weight of the shadow, and
may distort the image if it is too heavy.
Blend mode: Multiply
Opacity: 22% to 50% - depends on color of the item.
Angle: 130 to 120, use global light
Distance: 3 (256 thru 48x), Distance = 1 (32x, 24x)
Spread: 0
Size: 7 (256x thru 48x), Spread = 2 (32x, 24x)
}
width := image.GetWidth;
height := image.GetHeight;
//Get bitmap to hold final composited image and shadow
Result := TGPBitmap.Create(width, height, PixelFormat32bppARGB);
//Use ColorMatrix methods to "draw" the alpha image.
alphaMask := TImageEffects.GetAlphaMask(image);
try
//Blur the black and white shadow image
// shadow := TImageEffects.BoxBlur(alphaMask, radius);
shadow := TImageEffects.GaussianBlur(alphaMask, radius); //because Gaussian Blur is linearly-separable into two 1d kernels, it's actually faster than the box blur
finally
alphaMask.Free;
end;
//Draw
graphics := TGPGraphics.Create(Result);
try
//Draw the "shadow", using the passed in opacity value.
{
Color transformations are of the form
c = (r, g, b, a)
c' = (r, g, b, a)
c' = c*M
= (r, g, b, a, 1) * (0 0 0 0 0) //r
(0 0 0 0 0) //g
(0 0 0 0 0) //b
(1 1 1 1 0) //a
(0 0 0 0 1) //1
}
imageAttributes := TGPImageAttributes.Create;
{ cm := (
( 1, 0, 0, 0, 0),
( 0, 1, 0, 0, 0),
( 0, 0, 1, 0, 0),
( 0, 0, 0, 0.5, 0),
( 0, 0, 0, 0, 1)
);}
cm[0, 0] := 1; cm[0, 1] := 0; cm[0, 2] := 0; cm[0, 3] := 0; cm[0, 4] := 0;
cm[1, 0] := 0; cm[1, 1] := 1; cm[1, 2] := 0; cm[1, 3] := 0; cm[1, 4] := 0;
cm[2, 0] := 0; cm[2, 1] := 0; cm[2, 2] := 1; cm[2, 3] := 0; cm[2, 4] := 0;
cm[3, 0] := 0; cm[3, 1] := 0; cm[3, 2] := 0; cm[3, 3] := Opacity; cm[3, 4] := 0;
cm[4, 0] := 0; cm[4, 1] := 0; cm[4, 2] := 0; cm[4, 3] := 0; cm[4, 4] := 1;
imageAttributes.SetColorMatrix(
cm,
ColorMatrixFlagsDefault,
ColorAdjustTypeBitmap);
try
graphics.DrawImage(shadow,
MakeRectF(OffsetX, OffsetY, width, height), //destination rectangle
0, 0, //source (x,y)
width, height, //source width, height
UnitPixel,
ImageAttributes);
//Draw original image over-top of it's shadow
graphics.DrawImage(image, 0, 0);
finally
imageAttributes.Free;
end;
finally
graphics.Free;
end;
end;它使用该函数获取灰度alpha掩码:
class function TImageEffects.GetAlphaMask(image: TGPImage): TGPBitmap;
var
imageAttributes: TGPImageAttributes;
cm: TColorMatrix;
graphics: TGPGraphics;
Width, Height: UINT;
begin
{
Color transformations are of the form
c = (r, g, b, a)
c' = (r, g, b, a)
c' = c*M
= (r, g, b, a, 1) * (0 0 0 0 0)
(0 0 0 0 0)
(0 0 0 0 0)
(1 1 1 1 0)
(0 0 0 0 1)
}
imageAttributes := TGPImageAttributes.Create;
{ cm := (
( 0, 0, 0, 0, 0),
( 0, 0, 0, 0, 0),
( 0, 0, 0, 0, 0),
(-1, -1, -1, 1, 0),
( 1, 1, 1, 0, 1)
);}
cm[0, 0] := 0; cm[0, 1] := 0; cm[0, 2] := 0; cm[0, 3] := 0; cm[0, 4] := 0;
cm[1, 0] := 0; cm[1, 1] := 0; cm[1, 2] := 0; cm[1, 3] := 0; cm[1, 4] := 0;
cm[2, 0] := 0; cm[2, 1] := 0; cm[2, 2] := 0; cm[2, 3] := 0; cm[2, 4] := 0;
cm[3, 0] := -1; cm[3, 1] := -1; cm[3, 2] := -1; cm[3, 3] := 1; cm[3, 4] := 0;
cm[4, 0] := 1; cm[4, 1] := 1; cm[4, 2] := 1; cm[4, 3] := 0; cm[4, 4] := 1;
imageAttributes.SetColorMatrix(
cm,
ColorMatrixFlagsDefault,
ColorAdjustTypeBitmap);
width := image.GetWidth;
height := image.GetHeight;
Result := TGPBitmap.Create(Integer(width), Integer(height));
graphics := TGPGraphics.Create(Result);
try
graphics.DrawImage(
image,
MakeRect(0, 0, width, height), //destination rectangle
0, 0, //source (x,y)
width, height,
UnitPixel,
ImageAttributes);
finally
graphics.Free;
end;
end;核心是高斯模糊:
class function TImageEffects.GaussianBlur(const bitmap: TGPBitmap;
radius: Single): TGPBitmap;
var
width, height: Integer;
tempBitmap: TGPBitmap;
bdSource: TBitmapData;
bdTemp: TBitmapData;
bdDest: TBitmapData;
pSrc: PARGBArray;
pTemp: PARGBArray;
pDest: PARGBArray;
stride: Integer;
kernel: TKernel;
begin
// kernel := MakeGaussianKernel2d(radius);
kernel := MakeGaussianKernel1d(radius);
try
// Result := ConvolveBitmap(bitmap, kernel); brute 2d kernel
width := bitmap.GetWidth;
height := bitmap.GetHeight;
// GDI+ still lies to us - the return format is BGR, NOT RGB.
bitmap.LockBits(MakeRect(0, 0, width, height),
ImageLockModeRead,
PixelFormat32bppPARGB, bdSource);
//intermediate bitmap
tempBitmap := TGPBitmap.Create(width, height, PixelFormat32bppPARGB);
tempBitmap.LockBits(MakeRect(0, 0, width, height),
ImageLockModeWrite,
PixelFormat32bppPARGB, bdTemp);
//target bitmap
Result := TGPBitmap.Create(width, height, PixelFormat32bppARGB);
Result.LockBits(MakeRect(0, 0, width, height),
ImageLockModeWrite,
PixelFormat32bppPARGB, bdDest);
pSrc := PARGBArray(bdSource.Scan0);
pTemp := PARGBArray(bdTemp.Scan0);
pDest := PARGBArray(bdDest.Scan0);
stride := bdSource.Stride;
ConvolveAndTranspose(kernel, pSrc^, pTemp^, width, height, stride, True, EdgeActionClampEdges);
ConvolveAndTranspose(kernel, pTemp^, pDest^, height, width, stride, True, EdgeActionClampEdges);
//Unlock source
bitmap.UnlockBits(bdSource);
tempBitmap.UnlockBits(bdTemp);
Result.UnlockBits(bdDest);
//get rid of temp
tempBitmap.Free;
finally
kernel.Free;
end;
end;它需要一个一维内核:
class function TImageEffects.MakeGaussianKernel1d(radius: Single): TKernel;
var
r: Integer;
rows: Integer;
matrix: TSingleDynArray;
sigma: Single;
sigma22: Single;
sigmaPi2: Single;
sqrtSigmaPi2: Single;
radius2: Single;
total: Single;
index: Integer;
row: Integer;
distance: Single;
i: Integer;
begin
r := Ceil(radius);
rows := r*2+1;
SetLength(matrix, rows);
sigma := radius/3.0;
sigma22 := 2*sigma*sigma;
sigmaPi2 := 2*pi*sigma;
sqrtSigmaPi2 := Sqrt(sigmaPi2);
radius2 := radius*radius;
total := 0;
Index := 0;
for row := -r to r do
begin
distance := row*row;
if (distance > radius2) then
matrix[index] := 0
else
begin
matrix[index] := Exp((-distance)/sigma22) / sqrtSigmaPi2;
total := total + matrix[index];
Inc(index);
end;
end;
//Normalize the values
for i := 0 to rows-1 do
matrix[i] := matrix[i] / total;
Result := TKernel.Create(rows, 1, matrix);
end;然后,高斯函数的神奇之处在于它可以分为两个一维卷积:
class procedure TImageEffects.convolveAndTranspose(kernel: TKernel;
const inPixels: array of ARGB; var outPixels: array of ARGB; width,
height, stride: Integer; alpha: Boolean; edgeAction: TEdgeAction);
var
index: Integer;
matrix: TSingleDynArray;
rows: Integer; //number of rows in the kernel
cols: Integer; //number of columns in the kernel
rows2: Integer; //half row count
cols2: Integer; //half column count
x, y: Integer; //
r, g, b, a: Single; //summed red, green, blue, alpha values
row, col: Integer;
ix, iy, ioffset: Integer;
moffset: Integer;
f: Single;
rgb: ARGB;
ir, ig, ib, ia: Integer;
function ClampPixel(value: Single): Integer;
begin
Result := Trunc(value+0.5);
if Result < 0 then
Result := 0
else if Result > 255 then
Result := 255;
end;
begin
matrix := kernel.KernelData;
cols := kernel.Width;
cols2 := cols div 2;
for y := 0 to height-1 do
begin
index := y;
ioffset := y*width;
for x := 0 to width-1 do
begin
r := 0;
g := 0;
b := 0;
a := 0;
moffset := cols2;
for col := -cols2 to cols2 do
begin
f := matrix[moffset+col];
if (f <> 0) then
begin
ix := x+col;
if ( ix < 0 ) then
begin
if ( edgeAction = EdgeActionClampEdges ) then
ix := 0
else if ( edgeAction = EdgeActionWrapEdges ) then
ix := (x+width) mod width;
end
else if ( ix >= width) then
begin
if ( edgeAction = EdgeActionClampEdges ) then
ix := width-1
else if ( edgeAction = EdgeActionWrapEdges ) then
ix := (x+width) mod width;
end;
rgb := inPixels[ioffset+ix];
a := a + f * ((rgb shr 24) and $FF);
r := r + f * ((rgb shr 16) and $FF);
g := g + f * ((rgb shr 8) and $FF);
b := b + f * ((rgb ) and $FF);
end;
end;
if alpha then
ia := ClampPixel(a)
else
ia := $FF;
ir := ClampPixel(r);
ig := ClampPixel(g);
ib := ClampPixel(b);
outPixels[index] := MakeARGB(ia, ir, ig, ib);
Inc(index, height);
end;
end;
end;在使用示例时,在我的256x256源映像上:
image := TImageEffects.GenerateDropShadow(localImage, 14, 2.12132, 2.12132, 1.0);分析显示,88.62%的时间花在以下几行:
a := a + f * ((rgb shr 24) and $FF);
r := r + f * ((rgb shr 16) and $FF);
g := g + f * ((rgb shr 8) and $FF);
b := b + f * ((rgb ) and $FF);这是每像素α混合。
这让我认为有一个更好的方法来应用一个软阴影,应用模糊效果,毕竟,Windows和OSX在窗口实时应用了一个阴影。
发布于 2014-05-22 11:38:51
算法来自于这个博客条目:http://blog.ivank.net/fastest-gaussian-blur.html。当然,它正在实现最后一个也是最快的版本。:-)
它是直接从我的工作代码中复制的,所以外部假设可能反映了这一点。该函数返回一个更大的位图,以适应大小的增加。当然,在您的代码中,您需要相应地处理这个问题。它假定为32位alpha图片,但可以很容易地修改为只处理24位(CHANNELS常数和PixelFormat值)。
public static class DropShadow {
const int CHANNELS = 4;
public static Bitmap CreateShadow(Bitmap bitmap, int radius, float opacity) {
// Alpha mask with opacity
var matrix = new ColorMatrix(new float[][] {
new float[] { 0F, 0F, 0F, 0F, 0F },
new float[] { 0F, 0F, 0F, 0F, 0F },
new float[] { 0F, 0F, 0F, 0F, 0F },
new float[] { -1F, -1F, -1F, opacity, 0F },
new float[] { 1F, 1F, 1F, 0F, 1F }
});
var imageAttributes = new ImageAttributes();
imageAttributes.SetColorMatrix(matrix, ColorMatrixFlag.Default, ColorAdjustType.Bitmap);
var shadow = new Bitmap(bitmap.Width + 4 * radius, bitmap.Height + 4 * radius);
using (var graphics = Graphics.FromImage(shadow))
graphics.DrawImage(bitmap, new Rectangle(2 * radius, 2 * radius, bitmap.Width, bitmap.Height), 0, 0, bitmap.Width, bitmap.Height, GraphicsUnit.Pixel, imageAttributes);
// Gaussian blur
var clone = shadow.Clone() as Bitmap;
var shadowData = shadow.LockBits(new Rectangle(0, 0, shadow.Width, shadow.Height), ImageLockMode.ReadWrite, PixelFormat.Format32bppArgb);
var cloneData = clone.LockBits(new Rectangle(0, 0, clone.Width, clone.Height), ImageLockMode.ReadWrite, PixelFormat.Format32bppArgb);
var boxes = DetermineBoxes(radius, 3);
BoxBlur(shadowData, cloneData, shadow.Width, shadow.Height, (boxes[0] - 1) / 2);
BoxBlur(shadowData, cloneData, shadow.Width, shadow.Height, (boxes[1] - 1) / 2);
BoxBlur(shadowData, cloneData, shadow.Width, shadow.Height, (boxes[2] - 1) / 2);
shadow.UnlockBits(shadowData);
clone.UnlockBits(cloneData);
return shadow;
}
private static unsafe void BoxBlur(BitmapData data1, BitmapData data2, int width, int height, int radius) {
byte* p1 = (byte*)(void*)data1.Scan0;
byte* p2 = (byte*)(void*)data2.Scan0;
int radius2 = 2 * radius + 1;
int[] sum = new int[CHANNELS];
int[] FirstValue = new int[CHANNELS];
int[] LastValue = new int[CHANNELS];
// Horizontal
int stride = data1.Stride;
for (var row = 0; row < height; row++) {
int start = row * stride;
int left = start;
int right = start + radius * CHANNELS;
for (int channel = 0; channel < CHANNELS; channel++) {
FirstValue[channel] = p1[start + channel];
LastValue[channel] = p1[start + (width - 1) * CHANNELS + channel];
sum[channel] = (radius + 1) * FirstValue[channel];
}
for (var column = 0; column < radius; column++)
for (int channel = 0; channel < CHANNELS; channel++)
sum[channel] += p1[start + column * CHANNELS + channel];
for (var column = 0; column <= radius; column++, right += CHANNELS, start += CHANNELS)
for (int channel = 0; channel < CHANNELS; channel++) {
sum[channel] += p1[right + channel] - FirstValue[channel];
p2[start + channel] = (byte)(sum[channel] / radius2);
}
for (var column = radius + 1; column < width - radius; column++, left += CHANNELS, right += CHANNELS, start += CHANNELS)
for (int channel = 0; channel < CHANNELS; channel++) {
sum[channel] += p1[right + channel] - p1[left + channel];
p2[start + channel] = (byte)(sum[channel] / radius2);
}
for (var column = width - radius; column < width; column++, left += CHANNELS, start += CHANNELS)
for (int channel = 0; channel < CHANNELS; channel++) {
sum[channel] += LastValue[channel] - p1[left + channel];
p2[start + channel] = (byte)(sum[channel] / radius2);
}
}
// Vertical
stride = data2.Stride;
for (int column = 0; column < width; column++) {
int start = column * CHANNELS;
int top = start;
int bottom = start + radius * stride;
for (int channel = 0; channel < CHANNELS; channel++) {
FirstValue[channel] = p2[start + channel];
LastValue[channel] = p2[start + (height - 1) * stride + channel];
sum[channel] = (radius + 1) * FirstValue[channel];
}
for (int row = 0; row < radius; row++)
for (int channel = 0; channel < CHANNELS; channel++)
sum[channel] += p2[start + row * stride + channel];
for (int row = 0; row <= radius; row++, bottom += stride, start += stride)
for (int channel = 0; channel < CHANNELS; channel++) {
sum[channel] += p2[bottom + channel] - FirstValue[channel];
p1[start + channel] = (byte)(sum[channel] / radius2);
}
for (int row = radius + 1; row < height - radius; row++, top += stride, bottom += stride, start += stride)
for (int channel = 0; channel < CHANNELS; channel++) {
sum[channel] += p2[bottom + channel] - p2[top + channel];
p1[start + channel] = (byte)(sum[channel] / radius2);
}
for (int row = height - radius; row < height; row++, top += stride, start += stride)
for (int channel = 0; channel < CHANNELS; channel++) {
sum[channel] += LastValue[channel] - p2[top + channel];
p1[start + channel] = (byte)(sum[channel] / radius2);
}
}
}
private static int[] DetermineBoxes(double Sigma, int BoxCount) {
double IdealWidth = Math.Sqrt((12 * Sigma * Sigma / BoxCount) + 1);
int Lower = (int)Math.Floor(IdealWidth);
if (Lower % 2 == 0)
Lower--;
int Upper = Lower + 2;
double MedianWidth = (12 * Sigma * Sigma - BoxCount * Lower * Lower - 4 * BoxCount * Lower - 3 * BoxCount) / (-4 * Lower - 4);
int Median = (int)Math.Round(MedianWidth);
int[] BoxSizes = new int[BoxCount];
for (int i = 0; i < BoxCount; i++)
BoxSizes[i] = (i < Median) ? Lower : Upper;
return BoxSizes;
}
}我想它必须是直截了当的转换成德尔菲。
增编:根据博客上的评论,如果你有一个整数半径和三个方框,你实际上可以忘记DetermineBoxes()并使用:
BoxBlur(shadowData, cloneData, shadow.Width, shadow.Height, radius - 1);
BoxBlur(shadowData, cloneData, shadow.Width, shadow.Height, radius - 1);
BoxBlur(shadowData, cloneData, shadow.Width, shadow.Height, radius);与位图本身相比,它的执行时间可以忽略不计,但是.
发布于 2011-09-12 05:24:50
我询问代码的原因是看看您是使用了“快速位图”方法还是使用了GetPixel(), SetPixel()方法。
由于您已经讨论过这一点,所以我怀疑您是否能够在性能优化方面做更多的工作。GDI+只是不是为这样的像素操作场景而设计的。实际上,您应该考虑实现一个更简单的影子生成器,它看起来不那么花哨,但不会像处理器密集型的那样。
这在很大程度上取决于您的使用场景(您还没有真正描述):
您也可以在Paint.NET中尝试高斯模糊(它在大多数情况下使用GDI+ ),并在那里测量它的速度。我怀疑你能否使它比Paint.NET更快,所以它是一个很好的基准。
发布于 2014-05-22 13:09:16
如果这是纯粹的性能,那么您也可以考虑只转换源图像的矩形边缘条。这样,您就不会花费时间将图像的中心(隐藏)部分转移到屏幕上有可能绘制的部分。
https://stackoverflow.com/questions/7364026
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