The present disclosure relates to a deep learning-based image noise reduction device and method. The deep learning-based image noise reduction device according to an embodiment of the present disclosure includes: a first noise reduction module for acquiring a first image in which noise of an input image having an RGB color space is reduced; a first color space conversion module for acquiring a second image converted from the first image, so as to have a YCbCr color space; a second color space conversion module for acquiring a third image converted from the input image, so as to have only a luminance attribute from among attributes of the YCbCr color space; a second noise reduction module for acquiring a fourth image in which noise of the third image is reduced; an attribute combination module for generating a fifth image in which additional noise is reduced from the first image by using the luminance attribute and chrominance attribute of the second image and the luminance attribute of the fourth image; and a third color space conversion module for acquiring an output image converted from the fifth image, so as to have the RGB color space.