The paper solved the problems of less valid data in thermal infrared imager,impurity being on surface of specimen and uneasy dipartite corrosion area in image which happened in detection of structure parts’ hidden corrosion by thermal wave imaging.Firstly,the contrast of one unheated image was enhanced by self-adaptive mathematical morphology sharpening,and then location of the impurity was confirmed by change of the image grads.Secondly,the impurity in post-heated image sequences was filtered based on minimum of (5×5) template at the same impurity location.Thirdly,the sequence of images was transformed based on wavelet Daubechies9/7.Low frequency’s energy was cumulated and high frequency’s energy was reduced through analyzing distribution of the active thermal image’s energy.And then the thermal image was reconstructed.Finally,quantitative evaluation was presented between the reconstructed image and the original image.The experimental result indicates that the method can improve the quality of IR thermal image,reduce noise of IR thermal image,and obtain identified IR thermal image easily.