基于层分解的局部音调映射算子

Z. Chaithanya, G. Sreenivasulu
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引用次数: 0

摘要

图像的动态范围直接定义了它在图像中可以容纳的级别的数量。一般来说,使用的动态范围是256。定义图像的动态范围需要通过考虑图像将显示在其上的显示单元来完成。如果动态范围超过256,则该动态范围称为高动态范围。这个范围可以扩展到10000。这种图像不能在显示单元上显示,因为显示单元不能区分那么多的图像信息。这种图像信息需要进行转换,以便常规显示单元能够适应这种格式。这必须在不丢失太多信息的情况下完成。这个过程是非常关键的,是由几个色调映射算子完成的。音调映射算子有两种类型:全局和局部。全局色调映射操作符在整个图像中使用相同的映射函数,而局部色调映射操作符对图像的局部区域使用不同的映射函数。虽然全局TMOs的质量较好,但在转换后的图像中存在许多光晕效应。本文提出了一种基于分解的全局TMO来降低这些影响。图像被分解为两个层,基础层和细节层。为了提高转换图像的质量,提出了一种混合分解和优化的方法。
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Layer Decomposition based Local Tone Mapping Operator
Dynamic range of an image directly defines the number of levels it can accommodate in an image. In general, a dynamic range of 256 is in use. Defining dynamic range of an image need to be done by considering the display unit on which the image will be displayed on. If the dynamic range extends over 256, the dynamic range is said to be high dynamic range. This range may extend up to 10,000. This kind of images can’t be displayed on display units which can’t differentiate that many pictorial information. This kind of pictorial information need to be converted so that the regular display units can adapt the format. This must be done without losing much information. This process is very crucial and is done by several tone mapping operators. Tone mapping operators are of two types, global and local. Global tone mapping operators apply same mapping function throughout the image while the local tone mapping operators use different mapping functions for local regions of the image. Though the quality of global TMOs is better, there are many halo effects in the converted image. In this paper, a global TMO based on decomposition is proposed intended to reduce these effects. Image is decomposed in to two layers, base, and detail. A hybrid decomposition and optimization are proposed to improve the quality of converted image.
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