lundervold and Tai)模型在处理噪声图像时存在的缺陷,以及纹理部分和噪声部分之间的差异,将图像分解思想和ROF模型与LLT模型相结合,提出了一种新的分解去噪模型:DD(decomposition and denoising)模型。该模型在处理噪声图像时,将噪声图像分解为结构、纹理和噪声3部分,从而达到既去噪又能分解的目的。进一步通过仿真试验,验证了DD模型和算法的合理性及有效性。
Abstract
Through analysis shortcoming of the ROF(Rudin
Osher and Fatemi) model and LLT(Lysaker
Lundervold and Tai) model in denoising processing
and the difference between texture and noise
combining decomposition model
TV-norm and fourth-order PDE
the article proposes the DD(decomposition and denoising) modelWhen processing noise image
the new model decompose an noisy image into three parts
structure
texture and noise
and thas achieves denoising and decomposition Further through the experiments
we testify rationality and validity of the DD model and the algorithm