Your Search Results

Use this resource - and many more! - in your textbook!

AcademicPub holds over eight million pieces of educational content for you to mix-and-match your way.

Experience the freedom of customizing your course pack with AcademicPub!
Not an educator but still interested in using this content? No problem! Visit our provider's page to contact the publisher and get permission directly.

Using inverse image frequency for perception-based color image quantization

By: Dhatric, P.; Shah, B.; Raghavan, V.;

2004 / IEEE / 0-7803-8387-7

Description

This item was taken from the IEEE Conference ' Using inverse image frequency for perception-based color image quantization ' The process of selecting a small number of representative colors from an image of higher color resolution is called color image quantization. A well-known problem in quantizing images is to select the best representative colors that not only reduce the quantization error, but also account for the perception of human vision. The technique we propose effectively handles this problem by using the variation of colors in different regions of an image, in addition to the use of the color histogram, for effective perception and quantization. We introduce the property of inverse image frequency (IIF) for computing the representative colors of an image. IIF is based on the observation that colors within a color subset having non-uniform frequency distribution across the different regions of an image have better discriminating properties than those having uniform distribution. Our approach to incorporate the information derived from IIF can be combined with any standard quantization algorithm. The results show that our approach quantizes an image more effectively than using just the well-known median cut algorithm.