Patent RU-2342701-C1 (RU)
Inventor: TRAVINA ELENA IGOREVNA
IPC: G06K9/40
Filed: 2007-08-15
Granted: 2008-12-27
Abstract: FIELD: physics; image processing. 
     SUBSTANCE: present invention pertains to image processing, and in particular, to the method of complexing digital multispectral half-tone images. Method of complexing digital multispectral half-tone images, including obtaining the initial images, involves breaking down each initial image to low frequency and high frequency components, separate processing of low and high frequency component images, complexing of the components, based on the principle of weighted summation for each pixel, and formation of the resultant image. Each initial image is subjected to multiple-level decomposition by the Haar wavelet through fast discrete static two-dimensional wavelet-transformation with the objective obtaining an approximate component, which is a low frequency image component, and a family of detail components, which are high frequency image components. The values of the matrix of energy characteristics of pixels are determined at all decomposition levels for each image. All detail components are filtered and the detail components are corrected through adaptive change of the values of the detail components in accordance with the inter-level dynamics of their energy characteristics. The noise microstructure is removed through adaptive threshold cut of the values of detail components on each decomposition level. The correcting brightness function and the correcting contrast function are calculated for each decomposition level, the parameter of which is a value of the approximate component. Brightness of ranges of each decomposition level is smoothed out through transformation of the approximate components by correcting brightness functions. The detail components of the contrast correcting function are transformed. A weight function is calculated for each decomposition level, the parameter of which is a value of the energy characteristic. The component of each synthesised image for each pixel at each decomposition level is calculated by weighted summation of the corresponding components of decomposing initial images using weight functions. All detail components of the synthesised image are filtered, and the detail components are corrected through adaptive change of the values of detail components in accordance with the inter-level dynamics of their energy characteristics. Noise microstructures are eliminated through adaptive threshold cut of the values of detail components at each decomposition level. The brightness correcting function and the contrast correcting function are calculated, the parameter of which is the value of approximate components of the synthesised image. The approximate component of the correcting brightness function is transformed. The detail components of the contrast correcting function are transformed. The synthesised image is formed through reconstruction using reverse fast discrete static two-dimensional wavelet-transformation, applied to the detail components of the synthesised image and approximate component of the synthesised image. The brightness range of the resulting image is matched with parameters of the video system. 
     EFFECT: obtaining a high quality image, containing informative image elements of the same scene, obtained in different spectral ranges. 
     9 dwg