Fix severe boundary artifacts in Box filter caused by floating-point precision

[DavidDiao]

Description

This PR fixes a severe accuracy bug specifically affecting the Box filter during downsampling.

Users migrating from or comparing outputs with PIL/Pillow might notice that at certain downsampling ratios (e.g., 1000px -> 288px), pica produces periodic visual glitches.

The Root Cause

Unlike continuous filters (Lanczos, Bicubic) which gracefully decay to 0.0 at their window edges, the Box filter is a discrete step function. It relies on a hard cliff: a pixel is either fully included (weight 1.0) or completely excluded (weight 0.0).

When calculating the normalized distance of a boundary pixel to the center diff = (pxl + 0.5) - center:

1. Mathematically, a boundary pixel might have an exact distance of 0.5 or -0.5.
2. However, due to IEEE 754 double-precision floating-point arithmetic in JS, the distance is often computed as something like -0.49999999999999994.
3. The original Box filter logic Math.abs(x) < 0.5 evaluates this as true.

As a result, an out-of-bounds pixel that should have been discarded (weight 0.0) incorrectly receives a full weight of 1.0. This accidentally widens the averaging window by 1 extra pixel for certain periodic target pixels, drastically changing the denominator and introducing a neighboring color, causing the massive deviation.

The Fix

This PR implements a mathematically robust boundary extraction specifically to defend against floating-point jitter at exactly ±0.5 for the Box filter. By offsetting the Math.floor bounds by +0.5 (a standard technique used in PIL's C implementation), we physically exclude the floating-point-corrupted pixels from entering the accumulation loop.

Impact

• Box filter: Completely eliminates the periodic ~15 pixel value errors. Output now flawlessly matches Pillow's Box downsampling at the integer level.
• Other filters (Lanczos, Bicubic, etc.): Unaffected. Since continuous filters evaluate to 0.0 at x = support, floating-point boundary jitter does not impact their sum.