An electronic apparatus (100, 1000) comprising: a camera (120, 1030) including a first lens and a second lens capable of obtaining an image having a wider angle of view than the first lens; a display (130, 1010); a memory (110, 1040); and a processor configured to: provide a first image obtained using the first lens to the display (130, 1010) as a live view; obtain a second image using the second lens while providing the first image as a live view, wherein the second image includes a relatively wider range of a scene than the first image; obtain information regarding the second image and information regarding at least one object included in the second image using at least one neural network model; identify a screen type of the second image based on the information regarding the second image and the information regarding at least one object included in the second image, wherein the screen type indicates a classification of the scene included in the second image; identify a set of filters corresponding to the screen type of the second image; and correct the first image provided as the live view based on the identified set of filters, wherein the memory (110, 1040) includes a plurality of sets of filters corresponding to a plurality of screen types, wherein the processor is configured to identify the set of filters corresponding to the screen type of the second image from among the plurality of sets of filters, wherein the information regarding the second image comprises depth map information corresponding to the second image and saliency information corresponding to the second image; and wherein the processor is configured to obtain the depth map information by inputting the second image to a first neural network model, and obtain the saliency information by inputting the second image to a second neural network model. a camera (120, 1030) including a first lens and a second lens capable of obtaining an image having a wider angle of view than the first lens; a display (130, 1010); a memory (110, 1040); and a processor configured to: provide a first image obtained using the first lens to the display (130, 1010) as a live view; obtain a second image using the second lens while providing the first image as a live view, wherein the second image includes a relatively wider range of a scene than the first image; obtain information regarding the second image and information regarding at least one object included in the second image using at least one neural network model; identify a screen type of the second image based on the information regarding the second image and the information regarding at least one object included in the second image, wherein the screen type indicates a classification of the scene included in the second image; identify a set of filters corresponding to the screen type of the second image; and correct the first image provided as the live view based on the identified set of filters, provide a first image obtained using the first lens to the display (130, 1010) as a live view; obtain a second image using the second lens while providing the first image as a live view, wherein the second image includes a relatively wider range of a scene than the first image; obtain information regarding the second image and information regarding at least one object included in the second image using at least one neural network model; identify a screen type of the second image based on the information regarding the second image and the information regarding at least one object included in the second image, wherein the screen type indicates a classification of the scene included in the second image; identify a set of filters corresponding to the screen type of the second image; and correct the first image provided as the live view based on the identified set of filters, wherein the memory (110, 1040) includes a plurality of sets of filters corresponding to a plurality of screen types, wherein the processor is configured to identify the set of filters corresponding to the screen type of the second image from among the plurality of sets of filters, wherein the information regarding the second image comprises depth map information corresponding to the second image and saliency information corresponding to the second image; and wherein the processor is configured to obtain the depth map information by inputting the second image to a first neural network model, and obtain the saliency information by inputting the second image to a second neural network model.