Block Compressive Sensing for Solder Joint Images With Wavelet Packet Thresholding

This paper provides a novel method that can achieve better results in solder joint imagery compression and reconstruction. Wavelet packet decomposition is used to generate some frequency coefficients of images. The higher and lower frequency coefficients of the reconstruction signal are used separately to improve the reconstruction performance. A threshold that only relates to the higher frequency coefficients is defined to remove the noise in the reconstruction result in each iteration. A new control factor is further defined to control the threshold value. The control factor relates to the wavelet packet low-frequency coefficients and is updated by the wavelet packet low-frequency coefficients in each iteration. The experimental results reveal that the proposed algorithm is able to improve the performance in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) compared with classical algorithms in reconstruction of different types of solder joint images. When the sample rate is increased, the proposed method improves the reconstruction results and maintains low computational cost. The proposed algorithm can retain more image structure and achieve better results than some common methods.