时间: 2013年6月28日（周五）上午9:00
地点: 宝山校区E楼6层西座
讲座: Image Colorization Using Sparse Representation
演讲者: 香港科技大学 Oscar Chi-Lim Au 教授
演讲者简介： Oscar教授于1986年获得加拿大多伦多大学本科学位，于1988年和1991年先后获得美国普林斯顿大学硕士学位和博士学位，并于1992年加入香港科技大学任职。目前系香港科技大学电子与计算机工程学系教授，多媒体技术研究中心主任，计算机工程项目主任。于2011年获选为上海市“东方学者”，IEEE
Fellow。在国外学习工作的数十年中，Oscar教授主要致力于多媒体信号处理，其中包括图像视频编码与处理、亚像素渲染技术、压缩传感、高动态图像技术、数字水印及加密、基于视频编码标准的优化、GPU相关编码、软硬件协同设计等。讲座摘要：
Image colorization, which is the process of adding color to a monochrome image, used to be a timeconsuming and tedious task that requires tremendous user efforts. Traditionally, image colorization involves segmenting the given grayscale image into regions, then the user proceeds to assign a color to each region. Although it is expensive, colorization is widely used for coloring black-and-white photos and image recoloring. Existing colorization algorithms receive color cues in form of either scribbles that indicate colors of certain pixels or images with similar color; while their mechanisms to propagate chrominance information vary a lot.
In this work, we present a novel method to perform image colorization using sparse representation. We first trains an over-complete dictionary in YUV color space. Then taking a grayscale image and a subset of color pixels as inputs, our algorithm colorizes overlapping image patches via sparse representation; it is achieved by seeking sparse representations of patches that are consistent with both the grayscale image and the color pixels. We then aggregate the colorized patches with weights to obtain the colorization result. Our method leads to high-quality colorizations with small number of given color pixels. To demonstrate one of the applications of the proposed method, we apply it to transfer the color of one image onto another to obtain a visually pleasing image.
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