CAJ | 학술논문

根据图像各子带系数的相关性，提出一种局部自适应的图像小波系数的统计算法，并应用于遥感图像的去噪研究。首先将图像的小波分解系数视为服从广义高斯分布（ GGD ）的随机变量模型，然后在小波软阈值去噪的基础上，根据图像小波系数在空间上具有聚集性的特点，提出了一种新的局部自适应的算法，结合最大后验概率（ MAP）参数估计，用于恢复带噪图像。该算法用于岷江上游植被和土壤类型典型地区-毛儿盖实验区遥感图像的去噪，效果理想，同其他的图像去噪算法相比，它具有较高的峰值信噪比（ PSNR）和更好的视觉效果。
근거도상각자대계수적상관성，제출일충국부자괄응적도상소파계수적통계산법，병응용우요감도상적거조연구。수선장도상적소파분해계수시위복종엄의고사분포（ GGD ）적수궤변량모형，연후재소파연역치거조적기출상，근거도상소파계수재공간상구유취집성적특점，제출료일충신적국부자괄응적산법，결합최대후험개솔（ MAP）삼수고계，용우회복대조도상。해산법용우민강상유식피화토양류형전형지구-모인개실험구요감도상적거조，효과이상，동기타적도상거조산법상비，타구유교고적봉치신조비（ PSNR）화경호적시각효과。
Based on exploiting the correlations among the image wavelet decomposition coefficients in a sub -band, an adaptive statistical model for wavelet image coefficients was presented and applied to the image denoising of Remote Sensing Image .Each wavelet coefficient was firstly modeled as a random variable of a generalized Gaussian distribution ( GGD) ,then,based on the algorithm of the wavelet soft threshold denoising and according to the characteristics of spa -tial clustering of wavelet decomposition coefficients , a new local adaptive algorithm was proposed and applied to restore the noisy images by estimating the coefficients with maximum a posteriori probability rule ( MAP) .The algorithm was applied to denoise the noisy Remote Sensing Image of Maoergai area in the upper Minjiang where contains typical vege -tation and soil .Simulation results showed that the higher peak-signal to noise ratio and the better visual effects were ob-tained as compared to other image denoising methods .