Edge-preserving image decomposition using L1 fidelity with L0 gradient.

ABSTRACTWe present an image decomposition method using L1 fidelity term with L0 norm of gradient to decompose an image into base layer and detail layer. Generally, the L1 fidelity should be preferable to the L2 norm when the erroneous measurements exist. It is also reported that the L0 norm of gradient is a better prior term than total variation and the L2 norm of gradient. Therefore, we combine these two benefits to obtain our base layer by adopting our method using L1 fidelity and L0 gradient. Our image decomposition method can be regarded as the fundamental tool to generate multiple image editing applications, such as image denoising, edge detection, detail enhancement, cartoon JPEG artifact removal, local tone mapping, and contrast enhancement under low backlight condition. Experimental results show that our proposed method is promising as compared to the existing methods.