Research on wavelet-based image target detection & recognition technology

With the development of sensor technology, image fusion becomes increasingly important in complex battlefield environment. As traditional methods for precision-guided weapons systems exist defects of fuzzy detection, low recognition rate and poor real-time; this paper proposes a new fusion algorithm of combining wavelet transform with Canny operator. Firstly, the improved method detects the edge with Canny operator; Then using wavelet transform decomposes images; Next, adapts unique fusion rules to change wavelet coefficients of images, using weighted average algorithm for low-frequency component, while using a local area average variance criterion for high-frequency; Finally, using the inverse wavelet transform to obtain reconstructed images. Theoretical analysis and simulation results show: the improved method not only reduces the fuzziness and highlights target color, but also makes computational efficiency high, real-time good.