Object detection in smoke screen interference image sequences based on fractal

In the paper, a new method for the detection of moving weak targets in smoke screen interference image sequences is proposed. Edges in infrared image add a deterministic element to surface height degrading locally the surface fractality and leading to an underestimation of the local fractal dimension (LFD). A different local fractal dimension will be determined at edges even if the two segments incident to the edge have the same LFD. The concept is evaluated by comparing row-mean subtraction filter based on fractal theory with conventional operators such as, median subtraction filter. Results show a similar performance in a low-noise environment and superiority of the fractal operators in a high noise, the algorithms are effectively for smoke screen interference and are easy to be implemented by parallel processing hardware.