1. An image processing method that uses a processor to convert an image, the method comprising: performing, on each of multiple first dictionaries produced by dictionary learning, a process to approximate a first image by linear combination of elements of the first dictionary so as to produce a linear combination coefficient and thereby acquiring multiple linear combination coefficients; calculating, by the processor and for each of the multiple linear combination coefficients, a ratio between a largest coefficient element and a second-largest coefficient element among respective coefficient elements of the respective linear combination coefficients, the largest coefficient element having an absolute value that is largest among the respective coefficient elements and the second-largest coefficient element having an absolute value that is second-largest among the respective coefficient elements, thereby obtaining respective ratios of the multiple linear combination coefficients; selecting a specific linear combination coefficient, among the multiple linear combination coefficients, having the ratio that is largest among the respective ratios of the multiple linear combination coefficients; selecting, from multiple second dictionaries corresponding to the first dictionaries, a specific dictionary corresponding to the first dictionary for which the specific linear combination coefficient is selected; and converting the first image into a second image by using linear combination of the specific linear combination coefficient and elements of the specific dictionary.