Russian scientists develop technology to adapt TV images for individuals with color blindness
19.07.2025 | 16:30 |Specialists from Smart Engines, in collaboration with Russian scientists, have developed a unique television image processing technology. This innovation enables both individuals with normal color vision and those with color blindness to comfortably perceive on-screen content.
The proprietary algorithms, integral to this new technology, significantly enhance the discernibility of image details specifically for colorblind viewers. Simultaneously, the overall realistic color gamut and object recognition are preserved for viewers with typical color perception.
Approximately 300 million people worldwide experience color blindness, encountering difficulties in distinguishing certain hues, particularly when using smartphone, tablet, and television screens. Previously existing solutions generally focused solely on color correction, which often resulted in distortion of original colors and made object recognition challenging even for colorblind individuals (for instance, a red poppy might appear purple).
The novel Russian method prioritizes the naturalness of the image. It is based on modeling the characteristics of visual perception in individuals with impaired color vision (dichromats). The algorithms identify details that are poorly distinguishable for colorblind individuals and enhance their visibility by increasing contrast and adjusting brightness levels. Crucially, the original color gamut of the image remains unaltered. Consequently, individuals with color blindness can clearly discern key elements of the image, while other viewers observe the familiar picture without significant changes.
The efficacy of this new approach has been experimentally validated through the participation of volunteers with both normal and impaired color vision. Results indicated that 95% of respondents with normal vision and 90% of colorblind individuals reported that the processed images appeared significantly more realistic and closer to the original compared to the outcomes of standard adaptation technologies.
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