Spectral reconstruction algorithm

Abstract

The invention provides a spectral reconstruction algorithm. The spectral reconstruction algorithm comprises the following steps: (1) acquiring a CIE XYZ value of the CIE color space of a sample to be tested; (2) converting the CIE XYZ value of the sample to be tested into a CIEL*C*H* value according to preset rules; (3) carrying out sorting on a reference spectral value set formed by reference spectral values to obtain a corresponding subarea spectral value set; (4) according to a main-component analysis method, selecting three main components with large contribution rate in a subarea spectral value set as a first group of main components and calculating out a primary spectral value according to a reconstruction formula; (5) selecting subarea spectral values in the subarea spectral value set according to the primary spectral value, and selecting obtained screening spectral values to form a screening spectral value set; and (6) according to the main-component analysis method, selecting three main components with large contribution rate as a second group of main components in the screening spectral value set, and calculating to obtain a tested spectral value.

Description

technical field [0001] The invention relates to a spectral reflectance reconstruction algorithm, in particular to a spectral reconstruction algorithm. Background technique [0002] Spectral reflectance is an inherent property of an object, and the spectral reflectance of different objects is different, which can be called the "fingerprint" of the object. Spectral reflectance information of objects is often involved in the fields of printing, artwork reproduction, textiles and electronic commerce. Therefore, it is of great significance to measure the spectral reflectance of an object. In the prior art, the spectral reflectance of an object can be accurately measured by a spectrophotometer. However, the equipment such as a spectrophotometer is expensive and has low measurement efficiency, and the measurement can only be performed on objects with a certain size in a contact manner. Measure flat objects. [0003] In recent years, the method of predicting the object's spectral...

AI Technical Summary

Problems solved by technology

However, in the prior art, the principal component analysis method only uses a set of principal components to predict the spectral reflectance of all objects or within a pre-selected range, and the spectral reconstruction achieved in this way does not fully reflect the changes in object reflectance characteristics, and does not reflect the spectral characteristics of the boundary color well, making the reconstruction accuracy not high

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