Color Shift

Color shift, the unwanted alteration of an image's color balance, is a significant challenge across various image processing applications. Current research focuses on developing methods to accurately estimate and correct these shifts, employing techniques like UNet-based networks and variational inference within group equivariant convolutional neural networks to adapt to diverse data characteristics. These advancements aim to improve image quality in diverse contexts, from enhancing photos with over- or under-exposure to enabling more accurate color reproduction in virtual production environments and objective assessment of natural phenomena like leaf senescence. Ultimately, mitigating color shift is crucial for improving the accuracy and reliability of image analysis and computer vision systems.