Image Resolution Upscaler

Image resampling is the process of mapping a grid of pixels to a new coordinate system. When upscaling, the software must generate new pixel data where none existed before. Standard browser scaling often applies a generic bilinear filter, resulting in a distinct lack of sharpness or "muddy" textures.

This tool addresses the primary constraints of client-side upscaling:

• Interpolation Control: Choosing between Nearest Neighbor (for hard edges) and Bicubic (for continuous tones) is essential. We also offer Stepped Scaling, which performs the operation in multiple smaller passes to reduce artifacting.
• Frequency Restoration: Upscaling acts as a low-pass filter, attenuating high-frequency details. This tool utilizes a convolution kernel (Unsharp Mask) to artificially boost local contrast at boundaries, mitigating the perceived blur.
• Physical Output Targeting: Pixels are dimensionless until assigned a density. This tool calculates the maximum physical print size based on the target DPI (Dots Per Inch), preventing the common error of printing low-res images on large formats.

When preparing digital images for physical media, the relationship between pixels and physical dimensions is governed by the DPI (Dots Per Inch) constant. The required pixel width Wpx is calculated as:

To counteract the softening effect of bicubic interpolation, we apply a discrete convolution operation using a Laplacian kernel K. For a central pixel value pc and its neighbors pi:

Where S is the sharpening strength coefficient. A value of S > 0 enhances edge contrast, while S = 0 returns the original interpolated value.