# Contrast Optimization And Local Adaptation (COALA) for HDR Compression

## TL;DR

This paper introduces COALA, a novel HDR compression method that uses contrast optimization and local adaptation to significantly reduce dynamic range while preserving details and avoiding artifacts.

## Contribution

It presents a new regularized optimization framework for HDR compression that maintains local contrast and minimizes artifacts, advancing beyond existing methods.

## Key findings

- Capable of drastic dynamic-range compression
- Preserves fine details and local contrast
- Avoids common artifacts like halos and gradient reversals

## Abstract

This paper develops a novel approach for high dynamic-range compression. It relies on the widely accepted assumption that the human visual system is not very sensitive to absolute luminance reaching the retina, but rather responds to relative luminance ratios. Dynamic-range compression is then formulated as a regularized optimization in which the image dynamic range is reduced while the local contrast of the original scene is preserved. Our method is shown to be capable of drastic dynamic-range compression, while preserving fine details and avoiding common artifacts such as halos, gradient reversals, or loss of local contrast.