The paper presents the method of the valuation of random noise in the photogrammetric images, based on wavelets. The proposed method involves the analysis of the dynamics of the components of wavelet decomposition on ...The paper presents the method of the valuation of random noise in the photogrammetric images, based on wavelets. The proposed method involves the analysis of the dynamics of the components of wavelet decomposition on several resolution levels. The hypothesis was made that the noise-free images are characterized by systematically growing variances of the single components with growing decomposition. This hypothesis was. studied on several dozen fragments of airborne images recorded both with a photogrammetric analogue camera and digital camera. For all the studied photos taken with a digital camera, the hypothesis of growing variances of details was confirmed. The images from an analogue camera had different dynamics of variance, and the cause was recognized as random noise, caused by the grains from of the photographs. Referring to earlier applications of wavelets to noise evaluation, the proposed method is characterized by smaller dependence upon the structure and texture of the image.展开更多
文摘The paper presents the method of the valuation of random noise in the photogrammetric images, based on wavelets. The proposed method involves the analysis of the dynamics of the components of wavelet decomposition on several resolution levels. The hypothesis was made that the noise-free images are characterized by systematically growing variances of the single components with growing decomposition. This hypothesis was. studied on several dozen fragments of airborne images recorded both with a photogrammetric analogue camera and digital camera. For all the studied photos taken with a digital camera, the hypothesis of growing variances of details was confirmed. The images from an analogue camera had different dynamics of variance, and the cause was recognized as random noise, caused by the grains from of the photographs. Referring to earlier applications of wavelets to noise evaluation, the proposed method is characterized by smaller dependence upon the structure and texture of the image.
