3D CLUTs (Color Look Up Tables) are popular digital models used in image and video processing for color grading, simulation of analog films, and more generally for the application of various color transformations. The large size of these models leads to data storage issues when trying to distribute them on a large scale. In this paper, a highly effective lossy compression technique for 3D CLUTs is proposed. It is based on a multi-scale anisotropic diffusion reconstruction scheme. Our method exhibits an average compression rate of more than 99%, while ensuring visually indistinguishable differences with the application of the original CLUTs .
The development of an Image Processing (IP) application is a complex activity, which can be greatly alleviated by user-friendly graphical programming environments. Our major objective is to help IP experts reuse parts of their applications. A first work towards knowledge reuse has been to propose a suitable representation of the strategies of IP experts by means of IP plans (trees of tasks, methods and tools). This paper describes the CBR module of our interactive system for the development of IP plans. After a brief presentation of the overall architecture of the system and its other modules, we explain the distinction between an IP case and an IP plan, and give the selection criteria and functions that are used for similarity calculation. The core of the CBR module is a search/adaptation algorithm, whose main steps are detailed: retrieval of suitable cases, recursive adaptation of the selected one and memorization of new cases. The system's implementation is presently completed; its functioning is described in a session showing the kind of assistance provided by the CBR module during the development of a new IP application.
International audienceThe development of an image-processing (IP) application is a complex activity, which can be greatly alleviated by user-friendly graphical programming environments. The major objective of the work described in this paper is to help IP experts reuse parts of their applications. A first step towards knowledge reuse has been to propose a suitable representation of the strategies of IP experts by means of IP plans (trees of tasks, methods and tools). This paper describes the CBR module of an interactive system for the development of IP plans. After a brief presentation of the overall architecture of the system and its other modules, the authors explain the distinction between an IP case and an IP plan, and give the selection criteria and functions that are used for similarity calculation. The core of the CBR module is a search/adaptation algorithm, whose main steps are detailed: retrieval of suitable cases, recursive adaptation of the selected one and memorization of new cases. The system's implementation is presently completed; its functioning is described in a session showing the kind of assistance provided by the CBR module during the development of a new IP application
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