Abstract: This application provides an image processing method and an electronic device. The image processing method includes: acquiring a plurality of frames of original images; adding a reference coordinate image layer to a second field-of-view image; obtaining an image layer set according to a first field-of-view image, the second field-of-view image, and the reference coordinate image layer; processing, by using a deep learning network model, the image layer set to obtain a first enhanced image; and obtaining a second enhanced image according to the first enhanced image. In the method, since the added reference coordinate image layer reflects a mapping relationship between a field of view corresponding to the first field-of-view image and a field of view corresponding to the second field-of-view image, through the addition of the reference coordinate image layer, priori information can be added, so that different adjustments can be made subsequently according to different field-of-view relationships.

Abstract: This application provides an image processing method, apparatus, and an electronic device, relates to the field of image technologies. The method includes: obtaining a plurality of frames of original images, where the plurality of frames of original images include a small field-of-view image and a large field-of-view image; obtaining at least one first image block corresponding to the small field-of-view image and at least one second image block corresponding to the large field-of-view image; extracting texture information from the at least one first image block, and adding the extracted texture information to a target image block to obtain a target image, where the target image block is the second image block having a mapping relationship with the at least one first image block. The texture information in the small field-of-view image is added to the large field-of-view image to enhance details, thereby improving a definition of the large field-of-view image.