CAJ | 학술논문

为了在反卷积过程中正确地估计噪声的方差,该文构造一幅纯噪声图像跟实际的观测图像同步进行反卷积计算,并把纯噪声图像的方差作为观测图像中噪声方差的估计值来辅助计算规整化参数.针对规整化的各项异性,该文提出了能够保持两种噪声同步变化的特殊的规整化项.新的规整化项在迭代纯粹噪声图像时使用,这样确保每次迭代都可以保持人工噪声与实际图像噪声的统计特性相一致.在能够准确知道迭代过程中图像包含噪声的方差的时候,该文建立了规整化参数与图像噪声方差之间的关系式并转化成简单的解一元二次方程问题.实验证明新的算法不但更好地抑制了噪声而且避免了过平滑,基于时间步进法计算变分图像恢复的适应性被明显的提高了.
위료재반권적과정중정학지고계조성적방차,해문구조일폭순조성도상근실제적관측도상동보진행반권적계산,병파순조성도상적방차작위관측도상중조성방차적고계치래보조계산규정화삼수.침대규정화적각항이성,해문제출료능구보지량충조성동보변화적특수적규정화항.신적규정화항재질대순수조성도상시사용,저양학보매차질대도가이보지인공조성여실제도상조성적통계특성상일치.재능구준학지도질대과정중도상포함조성적방차적시후,해문건립료규정화삼수여도상조성방차지간적관계식병전화성간단적해일원이차방정문제.실험증명신적산법불단경호지억제료조성이차피면료과평활,기우시간보진법계산변분도상회복적괄응성피명현적제고료.
In order to correctly estimate the variance of noise in iteration, a pure synthesis noise as an image is synchronously iterated with the observation image in de-convolution, and it takes variance of pure noise image as the estimation of the variance of noise in observation image and computes the regularization parameter by the variance. A novel regularization term that can ensure the synchronous changing of the variance of the two noises is proposed in this article. The new regularization term is put into use only in iteration of pure noise image. Under the condition of knowing the variance of noise of image in iteration, this paper established the relationship between the variance of synthetic noise and the regularization parameter, and the relationship was converted to a simple quadratic equation. Experiments confirm that the new algorithm not only better restrains the noise but also avoids the over smoothing. The adaptability of total variation based image restoration is improved.