An Image Information Extraction Algorithm for Salt and Pepper Noise on Fractional Differentials

Abstract

An image information extraction algorithm on fractional differentials is put forward in this paper that is based on the characteristics of fractional differential in signal processing. This paper has extracted the information of salt and pepper noise images with various coefficients, and analyzed and compared it with the information extraction results of classic integer-order operators as Prewitt, Roberts and Sobel. Experiments have shown that not only the high-frequency marginal information can be extracted by extracting information with fractional differentials, just as it is extracted with integer-order operators, but the texture information can also be extracted from the smooth region. Besides, this algorithm is featured with great noise immunity against salt and pepper noises.

Fractional Order Correlation Algorithm's Accuracy Analysis

“…Therefore, from the description of the tracking it can conclude that, fractional differential could more accurately describe the memory nature of tracking comparing with the integral order one, and was imported to calculate the relevancy of the tracking. [13,14]…”

Fractional Order Ship Tracking Correlation Algorithm

“…Many researchers have found that, fractional derivative model can more accurately describe the nature of a memory and the genetic material and the distribution process than integer order derivative model [10]. The overall and memory characteristic of fractional are widely used in physics, chemistry, materials, fractal theory [11], image processing [12] and other fields. Currently, the analysis of fractional differential has become a new active researched area that aroused great attention of domestic and foreign scholars, and turned to be the world's leading edge and hot research field.…”