Nonsubsampled Contourlet Transform Based Infrared Image Super-Resolution

The present invention relates to a method and an apparatus for infrared image super-resolution transform based on nonsubsampled contourlet transform (NSCT), which transform a low resolution infrared (LR IR) image into high resolution infrared (HR IR) image through an NSCT method by using a sparse dictionary and a residual dictionary. According to the present invention, the method comprises : (A) a step of a raw sparse dictionary generation module receiving training LR and HR IR image sets to form a training high frequency map; (B) a step of the raw sparse dictionary generation module performing the NSCT of the training LR IR image to form a training LR coefficient block; (C) a step of the raw sparse dictionary generation module forming a training HR coefficient block from the training high frequency map; (D) a step of the raw sparse dictionary generation module using the training LR coefficient block to form a raw LR sparse dictionary and using the training HR coefficient block to form a raw HR sparse dictionary; (E) a step of a residual sparse dictionary generation module to form residual HR and LR sparse dictionaries; (F) a step of a test module receiving a test LR IR image to form a test LR coefficient block; and (G) a step of the test module calculating the formed HR coefficient block to form an estimated HR IR image.(S100) Training step(S110) Training LR IR image set(S120) Training HR IR image set(S130) Generate a training high frequency map(S140) Calculate a coefficient block(S150) Raw sparse dictionary pair(S160) Remaining sparse dictionary pair(S200) Test step(S210) Test LR IR image(S220) Calculate the coefficient block(S230) Form an estimated test HR IR imageCOPYRIGHT KIPO 2018