It is significant to realize effective image deblurring for improving the performance of the computational imaging system based on spherical optics. The image blurring model in the spherical optics is analyzed, and the image deblurring algorithm based on Wiener deconvolution is introduced. To deal with the problem that the signal-noise ratio (SNR) should be estimated accurately in the image deblurring based on Wiener deconvolution, a novel adaptive SNR estimation algorithm based on image denoising is proposed. The experiments are performed using the images acquired by Zemax software and the implemented prototype of the computational imaging system based on spherical optics. The results show that the noise variance and SNR can be estimated with high accuracy by using the proposed algorithm, and good image deblurring results can be achieved using Wiener deconvolution with the adaptively estimated SNR, so the clear and high resolution images can be acquired by the computational imaging system based on spherical optics after integrating the work presented.