Noise-Resistant Image Retrieval
Cyril Höschl, Jan Flusser · 2014
We present a content-based image retrieval method which is particularly designed for noisy images. The images are retrieved according to histogram similarity. To reach high robustness to noise, the histograms are described by novel features which are insensitive to convolution with a Gaussian kernel, i.e. insensitive to a Gaussian additive noise in original images. The advantage of the new method is demonstrated experimentally on real data.