Image upscaling apparatus using artificial neural network having multiple deconvolution layers and deconvolution layer pluralization method thereof

A deconvolution layer pluralization method for an image upscaling apparatus, the deconvolution layer pluralization method comprising:

• setting a plurality of convolution layers, the plurality of convolution layers configured to receive an input image or a feature map outputted by a previous convolution layer and output a feature map by extracting features from the input image or from the previous feature map;
• and
• setting a multilayer as a deconvolution layer configured to receive a final feature map outputted from a last convolution layer among the plurality of convolution layers and output an output image upscaled to have a predefined resolution higher than a resolution of the input image,
• wherein the setting of the multilayer comprises:
• setting a first partition layer, the first partition layer including a plurality of first filters and configured to output a first shuffle map, the first filters having a minimum size along an x-axis and a y-axis direction and having a same size as a z-axis direction size of the final feature map along a z-axis direction, the x-axis, y-axis, and z-axis directions representing width, height, and depth directions of the final feature map;
• and
• setting at least one second partition layer, the at least one second partition layer each including a plurality of second filters and configured to shuffle features in the x-axis and y-axis directions of the first shuffle map, the second filters having a size greater than that of the first filter in the x-axis and y-axis directions and having a number and size of the first filter in the z-axis direction.