GAUSSIAN MIXTURE MODEL BASED ILLUMINATION NORMALIZ

专利名称：GAUSSIAN MIXTURE MODEL BASED

ILLUMINATION NORMALIZATION FORGLOBAL ENHANCEMENT

发明人：Kamini Kanta Mohanty,Mahesh Kumar

Gellaboina,Jeremy Craig Wilson

申请号：US12164868申请日：20080630

公开号：US20110123133A1公开日：20110526

专利附图：

摘要：A method is presented for enhancing an image from an initial image, comprising

computing a first luminance level frequency distribution corresponding to plurality ofpixel constructing said initial image, representing said first luminance level frequencydistribution as a resultant of Gaussian model mixtures to assess relative utilization ofoverall luminance level across said initial image, computing a desired luminance levelfrequency distribution as a function of the relative utilization, computing a transferfunction to adjust the first luminance level frequency distribution to an enhancedluminance level as a function of desired level frequency distribution estimation, andapplying said transfer function globally to said initial image to provide an enhancedimage is. The first luminance level can be adapted to be linearized in a logarithmic form.In one embodiment, the model comprises one or more Gaussian functions. The initialimage can be a background image estimated from a sequence of images.

申请人：Kamini Kanta Mohanty,Mahesh Kumar Gellaboina,Jeremy Craig Wilson

地址：Bhubaneswar IN,Kurnool IN,Delta CA

国籍：IN,IN,CA

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