A computer implemented method of generating a high dynamic range, HDR, image, the method comprising: obtaining a plurality of images captured in different exposure degrees; generating at least one transformation matrix indicating regions corresponding between the plurality of images; determining a movement degree for each of the regions corresponding between the plurality of images, based on the transformation matrix; generating a blending map indicating a blending ratio of the plurality of images in each pixel, based on the determined movement degree; and generating the HDR image by blending the plurality of images, based on the blending map, characterized in that the generating of the at least one transformation matrix comprises: detecting, from the plurality of images, global feature points corresponding to features included in the plurality of images, and matching the global feature points corresponding between the plurality of images; searching for blocks corresponding between the plurality of images, based on a result of matching the global feature points; detecting center points of found blocks as local feature points, and matching the local feature points corresponding between the plurality of images; and generating the at least one transformation matrix, based on results of matching the global feature points and the local feature points. obtaining a plurality of images captured in different exposure degrees; generating at least one transformation matrix indicating regions corresponding between the plurality of images; determining a movement degree for each of the regions corresponding between the plurality of images, based on the transformation matrix; generating a blending map indicating a blending ratio of the plurality of images in each pixel, based on the determined movement degree; and generating the HDR image by blending the plurality of images, based on the blending map, characterized in that the generating of the at least one transformation matrix comprises: detecting, from the plurality of images, global feature points corresponding to features included in the plurality of images, and matching the global feature points corresponding between the plurality of images; searching for blocks corresponding between the plurality of images, based on a result of matching the global feature points; detecting center points of found blocks as local feature points, and matching the local feature points corresponding between the plurality of images; and generating the at least one transformation matrix, based on results of matching the global feature points and the local feature points. detecting, from the plurality of images, global feature points corresponding to features included in the plurality of images, and matching the global feature points corresponding between the plurality of images; searching for blocks corresponding between the plurality of images, based on a result of matching the global feature points; detecting center points of found blocks as local feature points, and matching the local feature points corresponding between the plurality of images; and generating the at least one transformation matrix, based on results of matching the global feature points and the local feature points. <EOS>