Hierarchical Color Correction for Camera Cell Phone Images

In this paper, we propose a hierarchical color correction algorithm for enhancing the color of digital images obtained from low quality digital image capture devices such as cell phone cameras. The proposed method is based on a multi layer hierarchical stochastic framework whose parameters are learned in an offline training procedure using the well-known expectation maximization (EM) algorithm. This hierarchical framework functions by first making soft assignments of images into defect classes and then processing the images in each defect class with an optimized algorithm. The hierarchical color correction is performed in three stages. In the first stage, global color attributes of the low quality input image are used in a Gaussian mixture model (GMM) framework to perform a soft classification of the image into M predefined global image classes. In the second stage, the input image is processed with a non-linear color correction algorithm that is designed for each of the M global clas...

• Type: Journal
• Year: 2008
• Where: TIP
• Authors: Hasib Siddiqui, Charles A. Bouman
• Keywords: Color Correction, Hierarchical Color Correction, Images, TIP 2008