High-Performance Image Processing with Halide: Building a Custom Sharpening Filter

Writing functional image processing code in C++ is relatively straightforward. You load an image, write some nested for loops to iterate over the width and height, apply your mathematical operations to the pixels, and save the result.

However, writing fast image processing code is an entirely different beast.

To squeeze every ounce of performance out of modern hardware, developers are usually forced to implement loop unrolling, manage cache locality, utilize platform-specific SIMD (Single Instruction, Multiple Data) intrinsics, and orchestrate complex multithreading. By the time you finish optimizing your pipeline, the original, elegant mathematical algorithm is entirely buried under a mountain of architecture-specific boilerplate.…