How to Improve Image Quality After Resizing in Java
Downscaling an image significantly can often result in a noticeable drop in quality. However, by adopting a divide and conquer approach, you can mitigate this issue, ensuring your resized images maintain a higher level of detail.
Divide and Conquer Method:
Instead of scaling the image directly to its final size, break down the process into smaller steps. For example, to resize a 650x748 image to fit within 60x60, start by scaling it down to 325x374 (50% of the original size). Then, scale it down again to 162x187 (50% of the previous size). Finally, scale it to its target size of 60x60, resulting in a much higher quality image than if the resizing was done in one large step.
Example Code:
public static BufferedImage getScaledInstanceToFit(BufferedImage img, Dimension size) { float scaleFactor = getScaleFactorToFit(img, size); return getScaledInstance(img, scaleFactor); } public static float getScaleFactorToFit(BufferedImage img, Dimension size) { float scale = 1f; if (img != null) { int imageWidth = img.getWidth(); int imageHeight = img.getHeight(); scale = getScaleFactorToFit(new Dimension(imageWidth, imageHeight), size); } return scale; } public static float getScaleFactorToFit(Dimension original, Dimension toFit) { float scale = 1f; if (original != null && toFit != null) { float dScaleWidth = getScaleFactor(original.width, toFit.width); float dScaleHeight = getScaleFactor(original.height, toFit.height); scale = Math.min(dScaleHeight, dScaleWidth); } return scale; }
Additional Tips:
- Use anti-aliasing: Anti-aliasing helps reduce jagged edges by blending adjacent pixels.
- High-quality rendering hints: Set the rendering hints to enable high-quality resizing and interpolation.
- Choose an appropriate interpolation algorithm: Use a high-quality interpolation algorithm such as bicubic or Lanczos for optimal results.
- Downscale moderately: Avoid excessive downscaling to preserve detail. Step down the image in smaller increments.
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