Pixel-wise Orthogonal Decomposition for Color Illumination Invariant and Shadow-free Image

TL;DR

This paper introduces a fast, pixel-wise orthogonal decomposition method to produce shadow-free, color illumination invariant images from single outdoor photos without needing shadow detection or learning.

Contribution

It presents a novel linear equation-based approach that computes illumination invariant vectors for each pixel, enabling shadow removal while preserving image details.

Findings

Effective shadow removal demonstrated on outdoor images

Outperforms state-of-the-art methods in experiments

Preserves texture and color in shadow-free images

Abstract

In this paper, we propose a novel, effective and fast method to obtain a color illumination invariant and shadow-free image from a single outdoor image. Different from state-of-the-art methods for shadow-free image that either need shadow detection or statistical learning, we set up a linear equation set for each pixel value vector based on physically-based shadow invariants, deduce a pixel-wise orthogonal decomposition for its solutions, and then get an illumination invariant vector for each pixel value vector on an image. The illumination invariant vector is the unique particular solution of the linear equation set, which is orthogonal to its free solutions. With this illumination invariant vector and Lab color space, we propose an algorithm to generate a shadow-free image which well preserves the texture and color information of the original image. A series of experiments on a diverse set of outdoor images and the comparisons with the state-of-the-art methods validate our method.