Abstract
A traditional problem with color image quantization techniques is their inability to handle smooth variations in intensity and chromaticity, leading to contours in the quantized image. To address this problem, this paper describes new techniques for augmenting the performance of a seminal color image quantization algorithm, the median-cut quantizer. Applying a simple texture analysis method from computer vision in conjunction with the median-cut algorithm using a new variant of a k-d tree, we show that contouring effects can be alleviated without resorting to dithering methods and the accompanying decrease in signal-to-noise ratio. The merits of this approach are evaluated using remotely sensed aerial imagery and synthetically generated scenes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
