… focused on finding saliency in natural images and predicting … saliency models, they all
assume the given image is clean … a noisy image instead of a clean image into existing saliency …

… 2, 13 and then investigate the stability of our saliency model for noisy images in Section 4. …
the stability of saliency models for noisy images. The same original test images from Bruce …

… All such automatic re-targeting methods rely on finding visual importance values for each …
Our saliency maps are more robust to noise than local intensity gradient based maps. There …

… quality of a noisy image is proposed. In the approach, visual saliency models of image patches
are … These two findings justify the usage of image patches and the gradient map in Q LF . …

… In general, they are structured in two levels, a top-down layer filters out noisy regions in
saliency maps created by the bottom-up layer. In most part of the cases, the top-down component …

… Finding the optimal segmentation is difficult because the … to small changes and noise in the
image. The positions of … frame but with independent Gaussian noise added at each iteration …

… On the noisy images the best numerical results shows the Robert’s edge detection, but
visually there is almost complete loss of boundaries on lowcontrast areas. Similar results showed …

… to predict human fixation points in images and such are ill-suited for finding regions of interest.
… Assuming the noise is uniform and Gaussian2 over the space of image patches, we have: …

… saliency cuts and the user provided sketches. In this step, access to image collections proves
critical since even in noisy … influence of background edges when finding a desired object. …

… , because the probability of finding relevant images in the bottom of ranked list is very low. …
image; 2) database saliency fails to distinguish relevant images as there exist no noisy images …