RANDOM NOISE ASSESSMENT IN AERIAL AND SATELLITE IMAGES

Random noise in aerial and satellite images is one of the factors, decreasing their quality. The noise level assessment in images is paid not enough attention. The method of numerical estimation of random image noise is considered. The object of the study is the image noise estimating method, based on harmonic analysis. The capability of using this method for aerial and satellite image quality assessment is considered. The results of the algorithm testing on model data and on real satellite images with different terrain surfaces are carried out. The accuracy estimating results for calculating the root-mean-square deviation (RMS) of random image noise by the harmonic analysis method are shown.

Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?

Objective: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. Materials and Methods: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. Results: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). Conclusion: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.

Seeing Global Motion in a Random Dot Image Sequence

In a stimulus with multiple moving elements, an observer may perceive that the whole stimulus moves in unison if (a) one can associate an element in one frame with one in the next (correspondence) and (b) a sufficient proportion of correspondences signal a similar motion direction (coherence). We tested the necessity of these two conditions by asking the participants to rate the perceived intensity of linear, concentric, and radial motions for three types of stimuli: (a) random walk motion, in which the direction of each dot was randomly determined for each frame, (b) random image sequence, which was a set of uncorrelated random dot images presented in sequence, and (c) global motion, in which 35% of dots moved coherently. The participants perceived global motion not only in the global motion conditions but also in the random image sequences, though not in random walk motion. The type of perceived motion in the random image sequences depends on the spatial context of the stimuli. Thus, although there is neither a fixed correspondence across different frames nor a coherent motion direction, observers can still perceive global motion in the random image sequence. This result cannot be explained by motion energy or local aperture border effects.