Chromaticity Gradient Mapping for Interactive Control of Color Contrast in Images and Video

要旨

We present a novel perceptually-motivated interactive tool for using color contrast to enhance details represented in the lightness channel of images and video. Our method lets users adjust the perceived contrast of different details by manipulating local chromaticity while preserving the original lightness of individual pixels. Inspired by the use of similar chromaticity mappings in painting, our tool effectively offers contrast along a user-selected gradient of chromaticities as additional bandwidth for representing and enhancing different details in an image. We provide an interface for our tool that closely resembles the familiar design of tonal contrast curve controls that are available in most professional image editing software. We show that our tool is effective for enhancing the perceived contrast of details without altering lightness in an image and present many examples of effects that can be achieved with our method on both images and video.

著者
Ruyu Yan
Princeton University, Princeton, New Jersey, United States
Jiatian Sun
Cornell University, Ithaca, New York, United States
Abe Davis
Cornell University, Ithaca, New York, United States
論文URL

https://doi.org/10.1145/3654777.3676340

動画

会議: UIST 2024

ACM Symposium on User Interface Software and Technology

セッション: 2. Vision-based UIs

Westin: Allegheny 2
4 件の発表
2024-10-15 19:40:00
2024-10-15 20:40:00