Develop Reference

best way to fade between two bitmaps in android

I have two bitmaps, namely bm1 and bm2, and I'd like to create (as quick as possible) another bitmap which is a fading mix between bm1 and bm2 where bm1 is weighted with weight and bm2 with 1-weight.
My current implementation is as follows:
private Bitmap Fade(Bitmap bm1, Bitmap bm2, double weight)
{
int width = bm1.getWidth();
int height = bm1.getHeight();
if (width != bm2.getWidth() || height != bm2.getHeight())
return null;
Bitmap bm = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
for (int y = 0; y < height; y++)
for (int x = 0; x < width; x++)
{
int pix_s = bm1.getPixel(x, y);
int pix_d = bm2.getPixel(x, y);
int r_s = (pix_s >> 16) & 0xFF;
int g_s = (pix_s >> 8) & 0xFF;
int b_s = pix_s & 0xFF;
int r_d = (pix_d >> 16) & 0xFF;
int g_d = (pix_d >> 8) & 0xFF;
int b_d = pix_d & 0xFF;
int r = (int)((1-weight) * r_s + weight * r_d);
int g = (int)((1-weight) * g_s + weight * g_d);
int b = (int)((1-weight) * b_s + weight * b_d);
int pix = 0xff000000 | (r << 16) | (g << 8) | b;
bm.setPixel(x, y, pix);
}
return bm;
}
As you can see, it simply sets the RGB components of each pixel of the generated image with an interpolation between the corresponding RGB components of pixels in bm1 and bm2.
However, this function is very slow as it scans all the pixels of the two input bitmaps.
Is there a more efficient way to do the same?
For instance, by someway acting onto the transparency attributes?

Here it shows you how to change the opacity of your bitmap, it changes the alpha channel of the RGB color.
and Here it shows you how to overlay in a canvas two bitmaps

android : editing images

In my app i want to edit images like brightness, contrast, etc. I got some tutorial and i am trying this to change contrast
public static Bitmap createContrast(Bitmap src, double value) {
// image size
int width = src.getWidth();
int height = src.getHeight();
// create output bitmap
Bitmap bmOut = Bitmap.createBitmap(width, height, src.getConfig());
// color information
int A, R, G, B;
int pixel;
// get contrast value
double contrast = Math.pow((100 + value) / 100, 2);
// scan through all pixels
for(int x = 0; x < width; ++x) {
for(int y = 0; y < height; ++y) {
// get pixel color
pixel = src.getPixel(x, y);
A = Color.alpha(pixel);
// apply filter contrast for every channel R, G, B
R = Color.red(pixel);
R = (int)(((((R / 255.0) - 0.5) * contrast) + 0.5) * 255.0);
if(R < 0) { R = 0; }
else if(R > 255) { R = 255; }
G = Color.red(pixel);
G = (int)(((((G / 255.0) - 0.5) * contrast) + 0.5) * 255.0);
if(G < 0) { G = 0; }
else if(G > 255) { G = 255; }
B = Color.red(pixel);
B = (int)(((((B / 255.0) - 0.5) * contrast) + 0.5) * 255.0);
if(B < 0) { B = 0; }
else if(B > 255) { B = 255; }
// set new pixel color to output bitmap
bmOut.setPixel(x, y, Color.argb(A, R, G, B));
}
}
// return final image
return bmOut;
calling it as :
ImageView image = (ImageView)(findViewById(R.id.image));
//image.setImageBitmap(createContrast(bitmap));
But i dont see any offect happening for the image. Can you please help where i am going wrong.
I saw the effectFactory from APi 14 . IS there something similar / any tutorial that can be used for older versions for image processing

There are three basic problems with this approach. The first two are coding issues. First, you are always calling Color.red, and there is no Color.green and Color.blue to be found in your code. The second issue is that this calculation is too repetitive. You assume the colors are in the range [0, 255], so it is much faster to create a array of 256 positions with the contrast calculated for each i in [0, 255].
The third issue is more problematic. Why did you consider this algorithm to improve contrast ? The results are meaningless for RGB, you might get something better in a different color system. Here are the results you should expect, with your parameter value at 0, 10, 20, and 30:
And here is a sample Python code to perform the operation:
import sys
from PIL import Image
img = Image.open(sys.argv[1])
width, height = img.size
cvalue = float(sys.argv[2]) # Your parameter "value".
contrast = ((100 + cvalue) / 100) ** 2
def apply_contrast(c):
c = (((c / 255.) - 0.5) * contrast + 0.5) * 255.0
return min(255, max(0, int(c)))
# Build the lookup table.
ltu = []
for i in range(256):
ltu.append(apply_contrast(i))
# The following "point" method applies a function to each
# value in the image. It considers the image as a flat sequence
# of values.
img = img.point(lambda x: ltu[x])
img.save(sys.argv[3])

Image processing effect time consuming

I apply sepia effect on image but when I click on button to apply its done but after 90 sec .
public static Bitmap effect(Bitmap src, int depth, double red, double green, double blue)
{
int width = src.getWidth();
int height = src.getHeight();
Bitmap bmOut = Bitmap.createBitmap(width, height, src.getConfig());
final double GS_RED = 0.3;
final double GS_GREEN = 0.59;
final double GS_BLUE = 0.11;
int A, R, G, B;
int pixel;
for(int x = 0; x < width; ++x) {
for(int y = 0; y < height; ++y) {
pixel = src.getPixel(x, y);
A = Color.alpha(pixel);
R = Color.red(pixel);
G = Color.green(pixel);
B = Color.blue(pixel);
B = G = R = (int)(GS_RED * R + GS_GREEN * G + GS_BLUE * B);
R += (depth * red);
if(R > 255) { R = 255; }
G += (depth * green);
if(G > 255) { G = 255; }
B += (depth * blue);
if(B > 255) { B = 255; }
bmOut.setPixel(x, y, Color.argb(A, R, G, B));
}}
return bmOut;
}

Oh, it appears that you are using the sample code on my blog: http://xjaphx.wordpress.com/2011/06/21/image-processing-photography-sepia-toning-effect/
The article means to demonstrate the how to implement the algorithm, so it certainly doesn't mention anything else.
As for performance problem, I suggest:
If you develop under Application Level (Java code..), use getPixels() setPixels() and manipulate the two-dimensional array. Well, in this sepia-toning, it might be up to only 5-10 seconds on emulator, on real device it might be 3 seconds.
It's preferable to do all image processing stuffs on NDK (like creating image processing library..), it will process much faster.
Anyway, have fun!

You could just place a semi-transparent orange/yellow rectangle ontop, it will achieve the same effect as your code above and you wont have to worry about processing time, you are using a mobile phone after all.
Its not solving your problem but its also no analysing and manipulating every pixels colour, your only issue would be saving the resulting image however this is done in a similar way

Intensity 0..255 of each pixel?

I have Black and White picture - RGB 565, 200x50.
as I can calculate the intensity 0..255 of each pixel?

That's what I meant, thanks. ma be this can someone help. I get Intensity 0..255 of each pixel and get the average.
Bitmap cropped = Bitmap.createBitmap(myImage, 503, 270,myImage.getWidth() - 955, myImage.getHeight() - 550);
Bitmap cropped2 = Bitmap.createBitmap(cropped, 0, 0,cropped.getWidth() , cropped.getHeight() / 2 );
final double GS_RED = 0.35;
final double GS_GREEN = 0.55;
final double GS_BLUE = 0.1;
int R, G, B;
int result = 0;
int g = 0;
int ff;
for(int x = 0; x < cropped2.getWidth(); x++)
{
int ff_y = 0;
for(int y = 0; y < cropped2.getHeight(); y++)
{
Pixel = cropped.getPixel(x, y);
R = Color.red(Pixel);
G = Color.green(Pixel);
B = Color.blue(Pixel);
ff = (int)(GS_RED * R + GS_GREEN * G + GS_BLUE * B) ;
ff_y += ff;
}
result += ff_y;
g = result / (cropped2.getWidth()*cropped2.getHeight());
}
Toast.makeText(this, "00" + g, Toast.LENGTH_LONG).show();

You could try to convert it using a color model with a luminance and two chrominance components. The luminance component accounts for the brightness while the two chrominance components represent the colors. You might want to check out http://en.wikipedia.org/wiki/YUV.
Otherwise: If I'm correct, the white over gray to black colors have equal values in a RGB format which has the same number of bits for each channel (e.g. from (0, 0, 0) to (255, 255, 255)). Assuming this is true you could just take one of the channels to represent the intensity as you could determine the other values from that. No guarantee if this works.
Edit:
I wrote a snippet demonstrating the idea described above. I used RGB888 but it should also work with RGB 565 after dropping the assertion and modifying the maximum intensity of a pixel as described in the comments. Mind that there are only 2^5 different intensity levels per pixel. Hence you might want to use a scaled version of the average intensity.
I tested it using images from http://www.smashingmagazine.com/2008/06/09/beautiful-black-and-white-photography/. I hope it will work out porting this to android for you.
// 2^5 for RGB 565
private static final int MAX_INTENSITY = (int) Math.pow(2, 8) - 1;
public static int calculateIntensityAverage(final BufferedImage image) {
long intensitySum = 0;
final int[] colors = image.getRGB(0, 0, image.getWidth(),
image.getHeight(), null, 0, image.getWidth());
for (int i = 0; i < colors.length; i++) {
intensitySum += intensityLevel(colors[i]);
}
final int intensityAverage = (int) (intensitySum / colors.length);
return intensityAverage;
}
public static int intensityLevel(final int color) {
// also see Color#getRed(), #getBlue() and #getGreen()
final int red = (color >> 16) & 0xFF;
final int blue = (color >> 0) & 0xFF;
final int green = (color >> 8) & 0xFF;
assert red == blue && green == blue; // doesn't hold for green in RGB 565
return MAX_INTENSITY - blue;
}

How do you get the RGB values from a Bitmap on Android?

I want to get RGB values of a Bitmap on Android but I can't do this so far. My aim is to obtain RGB values for each pixel of a Bitmap. Is there any specific function for Android or anything else?
Also I wonder that do I need colorMatrix() function?
It is very important for my project.

Bitmap#getPixel(x, y) returns an int with the colour values and alpha value embedded into it.
int colour = bitmap.getPixel(x, y);
int red = Color.red(colour);
int green = Color.green(colour);
int blue = Color.blue(colour);
int alpha = Color.alpha(colour);

This may be slightly late, but to clear up the confusion with the use of &0xff:
In Java ints are 32 bits, so the (A)RGB values for each pixel are packed in 4 bytes.
In other words, a pixel with the values R(123), G(93), B(49) = FF7B 5D31 in the ARGB_8888 model. Where Alpha = FF, R = 7B, G = 5D, B = 31. But this is stored as an int as -8692431.
So, to extract the Green value from -8692431, we need to shift the 5D by 8 bits to the right, as you know. This gives 00FF 7B5D. So, if we were just to take that value we would be left with 16743261 as our Green value. Therefore, we bitwise-and that value with the mask of 0xFF (which is equivalent to 0000 00FF) and will result in 00FF 7B5D being 'masked' to 0000 005D. So we have extracted our Green value of 5D (or 93 decimal).
We can use the same mask of 0xFF for each extraction because the values have all been shifted to expose the desired two bytes as the least significant. Hence the previously suggested code of:
int p = pixel[index];
int R = (p >> 16) & 0xff;
int G = (p >> 8) & 0xff;
int B = p & 0xff;
If it makes it clearer, you can perform the equivalent operation of:
int R = (p & 0xff0000) >> 16;
int G = (p & 0x00ff00) >> 8;
int B = (p & 0x0000ff) >> 0;
For brevity, the extra 0s can be dropped, and it can be written as
int R = (p & 0xff0000) >> 16;
int G = (p & 0xff00) >> 8;
int B = p & 0xff;
Note however, that alternative colour models may be used, such as RGB_555 which stores each pixel as just 2 bytes, with varying precision for the RGB channels. So you should check the model that your bitmap is using before you perform the extraction, because the colours may be stored differently.

This is how I am trying to get that value. Use bitmap.getPixel() to get the corresponding bitmap in
integer array. By using bitwise rotation operation, we will get RGB values.
int[] pix = new int[picw * pich];
bitmap.getPixels(pix, 0, picw, 0, 0, picw, pich);
int R, G, B,Y;
for (int y = 0; y < pich; y++){
for (int x = 0; x < picw; x++)
{
int index = y * picw + x;
int R = (pix[index] >> 16) & 0xff; //bitwise shifting
int G = (pix[index] >> 8) & 0xff;
int B = pix[index] & 0xff;
//R,G.B - Red, Green, Blue
//to restore the values after RGB modification, use
//next statement
pix[index] = 0xff000000 | (R << 16) | (G << 8) | B;
}}

Arbitrary Bitmap Color Handling
You can read about the various Color methods here that will extract the components of color from a pixel int.
You might want to apply a filter to the bitmap, and return a byte array. Otherwise, you can cut this example down to the for-loop and roll through the pixels generating your array of bytes.
private byte[] rgbValuesFromBitmap(Bitmap bitmap)
{
ColorMatrix colorMatrix = new ColorMatrix();
ColorFilter colorFilter = new ColorMatrixColorFilter(
colorMatrix);
Bitmap argbBitmap = Bitmap.createBitmap(bitmap.getWidth(), bitmap.getHeight(),
Bitmap.Config.ARGB_8888);
Canvas canvas = new Canvas(argbBitmap);
Paint paint = new Paint();
paint.setColorFilter(colorFilter);
canvas.drawBitmap(bitmap, 0, 0, paint);
int width = bitmap.getWidth();
int height = bitmap.getHeight();
int componentsPerPixel = 3;
int totalPixels = width * height;
int totalBytes = totalPixels * componentsPerPixel;
byte[] rgbValues = new byte[totalBytes];
#ColorInt int[] argbPixels = new int[totalPixels];
argbBitmap.getPixels(argbPixels, 0, width, 0, 0, width, height);
for (int i = 0; i < totalPixels; i++) {
#ColorInt int argbPixel = argbPixels[i];
int red = Color.red(argbPixel);
int green = Color.green(argbPixel);
int blue = Color.blue(argbPixel);
rgbValues[i * componentsPerPixel + 0] = (byte) red;
rgbValues[i * componentsPerPixel + 1] = (byte) green;
rgbValues[i * componentsPerPixel + 2] = (byte) blue;
}
return rgbValues;
}

One for statement less :D
imagen.getPixels(pix, 0, picw, 0, 0, picw, pich);
for (i = 0; i < pix.length; i++) {
r = (pix[i]) >> 16 & 0xff;
g = (pix[i]) >> 8 & 0xff;
b = (pix[i]) & 0xff;
}

In addition to #Cobbles' answer, you can also use Bitmap#getColor(x, y) and a Color object.
for (int y = 0; y < bitmap.getHeight(); y++) {
for (int x = 0; x < bitmap.getWidth(); x++) {
Color color = bitmap.getColor(x, y);
float red = color.red();
float green = color.green();
float blue = color.blue();
float alpha = color.alpha();
Log.d(TAG, String.format(
"(R, G, B, A) = (%f, %f, %f, %f)", red, green, blue, alpha
));
}
}
With above code, you can get float (0..1) RGBA values. When you just want to get integer (0..255) values, #Cobble's way is rather straight forward (recommended). Though there is still a way to get integer values with this Color object by using Color#toArgb.
for (int y = 0; y < bitmap.getHeight(); y++) {
for (int x = 0; x < bitmap.getWidth(); x++) {
int color = bitmap.getColor(x, y).toArgb();
int red = Color.red(color);
int green = Color.green(color);
int blue = Color.blue(color);
int alpha = Color.alpha(color);
Log.d(TAG, String.format(
"(R, G, B, A) = (%3d, %3d, %3d, %3d)", red, green, blue, alpha
));
}
}