Spectral Sensitivity

Spectral sensitivity research focuses on understanding and modeling how cameras and the human visual system respond to different wavelengths of light. Current research emphasizes developing accurate methods for estimating camera spectral sensitivities, even without direct access to the camera hardware, often leveraging machine learning techniques like neural radiance fields (NeRFs) and autoencoders to achieve this. These advancements are crucial for improving image and video processing, particularly in applications like computer vision, where accurate color representation is essential for tasks such as object recognition and scene reconstruction, and for developing more perceptually efficient compression algorithms.