基于小波与双三次插值的高温锻件红外图像增强方法

提出了一种基于小波变换和双三次插值的图像处理方法，该方法利用离散小波将原图像分解成低频子带与高频子带，然后对原图像及这些子带分别进行双三次插值,同时提出增加一个中间步骤来估算高频子带，即扣除原低分辨率图像和插值后的LL子带中的相同成分而得到不同成分的图像（高频成分），然后利用不同成分的图像对高频子带LH、HL及HH分别进行校正融合,并通过小波逆变换对这些图像进行融合重构。该方法不仅能够有效地消除图像噪声,改善细节信息，而且能够最大限度地保留边缘信息和增加图像的清晰度。最后运用该方法和传统算法分别对核电主管道高温锻件和小型高温锻件的红外图像进行增强处理，实验结果验证了该方法的可行性及优越性。

Infrared Image Enhancement Algorithm for Hot Forgings Based on Wavelet Transform and Bicubic Interpolation

A new image resolution enhancement technique was presented based on wavelet transform and bicubic interpolation, which used discrete wavelet to decompose the original images into different subbands, and then the original images and these subbands were bicubic interpolated. Meanwhile, an intermediate stage for estimating the high-frequency subbands was proposed in image processing, the differences among the low low(LL) subband images and the low-resolution input images wers extracted and this difference image(high-frequency components) was used in the intermediate processes to correct the estimated high-frequency components such as low high(LH), high low(HL) and high high(HH). At last, all these images were combined by using inverse wavelet transform. This method may effectively eliminate image noises and improve the image detail informations, and may preserve more edge informations and obtain a sharper image. The processing results of infrared images from main pipeline forgings of nuclear power and small hot forgings show that the superiority of the proposed algorithm on improving the quality of infrared images compared with the conventional image enhancement methods.