For the problem of large decoding errors generated by the image compression based on Bayesian compressed sensing with local optimization

a new codec uniting the optimal directional selection of wavelet sub-bands with Bayesian compressed sensing is proposed

which reduces the error of the decoded images and increases the accuracy of the codec. According to the correlation differences between the low-frequency and the high-frequency sub-bands

we use a respective codec for each of them. Low-frequency coefficients contain the images' main information. With the purpose of avoiding local optimization

we apply the correlation of the low-frequency sub-band

introducing the optimal direction selection codec to the low-frequency coefficients

and combining Bayesian compressed sensing based on the wavelet transform to deal with high-frequency coefficients containing details of images. The experimental results show that in the case without increasing the bit rate

the decoded images using the proposed method have good subjective quality

and the PSNR and SSIM of images are improved to some extent.