How to Achieve Effective Color Quantization for Animated GIFs in Java?
Effective Color Quantization for Animated GIFs
In Java, the quantization algorithm you mentioned (found at http://www.java2s.com/Code/Java/2D-Graphics-GUI/Anefficientcolorquantizationalgorithm.htm) appears to be lacking precision for images with more than 256 colors. To enhance color quantization, consider the following alternatives:
Alternative Algorithms:
- Median cut
- Population
- K-means
Approach for Fast and Efficient Quantization:
- Convert to 15-bit RGB (or 5:6:5 scheme for better results).
- Create a histogram to count pixel occurrences.
- Reorder the histogram to eliminate zero values.
- Sort the histogram to arrange colors in descending order based on pixel count.
- Create a palette of N colors, adding only unique colors from the sorted histogram until the palette is complete.
- Map each color in the original image to the closest color in the palette.
- Recolor the image using the color mapping table.
Sample Code in C :
// Histogram and index arrays DWORD his[32768]; DWORD idx[32768]; // Recolor mapping table BYTE recolor[32][32][32]; // Extract 15-bit RGB from 32-bit RGB cc=((cc>>3)&0x1F)|((cc>>6)&0x3E0)|((cc>>9)&0x7C00); // Histogram counting his[cc]++; // Reorder and sort histogram for (x=0,y=0;y<32768;y++) { his[x]=his[y]; idx[x]=idx[y]; if (his[x]) x++; } hists=x; for (i=1;i;) for (i=0,x=0,y=1;y<hists;x++,y++) if (his[x]<his[y]) { i=his[x]; his[x]=his[y]; his[y]=i; i=idx[x]; idx[x]=idx[y]; idx[y]=i; i=1; } // Create color palette for (i0=0,x=0;x<hists;x++) { cc=idx[x]; b= cc &31; g=(cc>> 5)&31; r=(cc>>10)&31; c0.db[0]=b; c0.db[1]=g; c0.db[2]=r; c0.dd=(c0.dd<<3)&0x00F8F8F8; // Find closest color in palette int dc=-1; DWORD ii=0; for (a=0,i=0;i<i0;i++) { aa=int(BYTE(c1.db[0]))-int(BYTE(c0.db[0])); if (aa<=0) aa=-aa; a =aa; aa=int(BYTE(c1.db[1]))-int(BYTE(c0.db[1])); if (aa<=0) aa=-aa; a+=aa; aa=int(BYTE(c1.db[2]))-int(BYTE(c0.db[2])); if (aa<=0) aa=-aa; a+=aa; if ((dc<0)||(dc>a)) { dc=a; ii=i; } } recolor[r][g][b]=ii; } // Recolor image using mapping table pyx [y][x]=lcolor[recolor[r][g][b]];
This approach provides faster and more accurate color quantization. The specific algorithm and parameters to use may vary depending on the input images and desired outcomes.
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