According to implementations of the present disclosure, a scheme for super-resolution image reconstruction is proposed. According to the scheme, an input image having a first resolution is obtained. A reversible neural network is trained with the input image, wherein the reversible neural network is configured to generate an
intermediate image having a second resolution and first high-frequency information based on the input image, and the second resolution is lower than the first resolution. Subsequently, an output image having a third resolution is generated based on the input image and second high-frequency information subject to a predetermined distribution by using an inverse network of the trained reversible neural network, wherein the third resolution is higher than the first resolution. The scheme can effectively process a low-resolution image obtained by an unknown downsampling method, thereby obtaining a high-quality high-resolution image.