When Color Constancy Goes Wrong: Correcting Improperly White-Balanced Images
This paper focuses on correcting a camera image that has been improperly white-balanced. This situation occurs when a camera's auto white balance fails or when the wrong manual white-balance setting is used. Even after decades of computational color constancy research, there are no effective solutions to this problem. The challenge lies not in identifying what the correct white balance should have been, but in the fact that the in-camera white-balance procedure is followed by several camera-specific nonlinear color manipulations that make it challenging to correct the image's colors in post-processing. This paper introduces the first method to explicitly address this problem. Our method is enabled by a dataset of over 65,000 pairs of incorrectly white-balanced images and their corresponding correctly white-balanced images. Using this dataset, we introduce a k-nearest neighbor strategy that is able to compute a nonlinear color mapping function to correct the image's colors. We show our method is highly effective and generalizes well to camera models not in the training set.
Code (1)
Tasks
Color ConstancySimilar Papers 제목 키워드 기반
Beyond White: Ground Truth Colors for Color Constancy Correction
A limitation in color constancy research is the inability to establish ground truth colors for evaluating corrected images. Many existing datasets contain images of scenes with a color chart included; however, only the c…
Color ConstancyDeep Neural Models for color discrimination and color constancy
Color constancy is our ability to perceive constant colors across varying illuminations. Here, we trained deep neural networks to be color constant and evaluated their performance with varying cues. Inputs to the network…
Color ConstancyMIMT: Multi-Illuminant Color Constancy via Multi-Task Local Surface and Light Color Learning
The assumption of a uniform light color distribution is no longer applicable in scenes that have multiple light colors. Most color constancy methods are designed to deal with a single light color, and thus are erroneous …
Color ConstancyEdge DetectionMulti-Task LearningThe Past and the Present of the Color Checker Dataset Misuse
The pipelines of digital cameras contain a part for computational color constancy, which aims to remove the influence of the illumination on the scene colors. One of the best known and most widely used benchmark datasets…
Color ConstancyInvestigating Color Illusions from the Perspective of Computational Color Constancy
Color constancy and color illusion perception are two phenomena occurring in the human visual system, which can help us reveal unknown mechanisms of human perception. For decades computer vision scientists have developed…
Color Constancy