Hue rotation (HR) and hue blending (HB): Real‐time image enhancement methods for digital component video signals to support red‐green color‐defective observers

The mutual understanding of color‐normal observers (CNOs) and color‐defective observers (CDOs) is now essential because personal color information display environments have been widely adopted. However, existing tools for CDOs offer only color discrimination; they fail to support color impression (ie, saturation and contrast). Therefore, we need a novel tool that offers help in distinguishing opponent colors, while preserving color saturation. We introduce two key techniques for realizing this difficult goal. The former is the repeated sequential display of the original and processed images to support the formation of unified correct percepts that provide discrimination of both red‐green and yellow‐blue opponent colors. One image, ie, original, exhibits correct yellow‐blue but distorted red‐green information for CDOs while the other, ie, processed, provides synthesized distinguishable red‐green but confusable yellow‐blue information for CDOs; here, hue rotation (HR) is useful for advanced users whereas hue blending (HB) is suitable for general. The latter is realized by the real‐time video processing available on smartphones; our algorithms support direct processing of the digital component video signal formats (eg, Y, CR, and CB). Subjective tests suggest that the two above‐mentioned algorithms will, along with embedding a lightweight real‐time dichromatic simulation facility for CNOs, greatly help the mutual understanding of CNOs and CDOs. Mutual understanding between color‐normal observers and color‐defective observers (CDOs) has become critical because personal color information display environments have become pervasive in the last decade. Therefore, we propose two simple and lightweight real‐time algorithms for smartphones to well enhance the red‐green color perception of CDOs, ie, color contrast and categorization.