Re-sampling by Downscaling Lowers Image Quality?

The goal here is to reduce the size of an image while preserving its quality in a browser environment. The issue arises when scaling down an image using HTML5 canvas, resulting in image degradation.

Downscaling vs Interpolation

Downscaling and interpolation are distinct techniques. Downscaling refers to reducing the image dimensions by combining pixels in the source image to create fewer pixels in the destination image, while interpolation is the creation of new pixels in the destination image when scaling up. In the context of downscaling, interpolation is irrelevant.

Pixel Perfect Downscaling

The problem lies in browsers' implementation of downscaling, which uses a simple method that picks a single pixel from the source image to represent each pixel in the destination image. This can result in loss of detail and noise.

Solution: Pixel Perfect Downscaling Algorithm

A pixel-perfect downscaling algorithm ensures that all source pixels contribute to one, two, or four destination pixels, depending on the overlap of pixels. This algorithm takes each source pixel and computes its weight and next weight within the target pixel and its adjacent pixels. Weights are then used to calculate the contribution of the source pixel to the target pixels.

Implementation Details

The provided JavaScript code offers a pixel-perfect downscaling algorithm. It creates a float32 array to store the intermediate pixel values, which is three times the size of the target image. This can be memory intensive for large images.

Limitations

While this algorithm provides high-quality downscaling, it can be slow to process large images due to the use of the getImageData and putImageData functions.

Additional Considerations

For smaller images, downscaling can be performed multiple times using HTML5 canvas's built-in scaling mechanisms, as they optimize for small images. For larger images, consider using other methods such as CSS or WebGL for downscaling.