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The color vision deficiency, popularly called daltonism or color-blindness, manifests with limited color discrimination ranging from slightly reduced to complete loss of color. The accessibility of color-coded digital information is still an unsolved issue for approximately 200 million users affected by this condition. The previous research yielded various image adaptation methods, referred to in the literature as daltonization methods that aim to compensate for weak color perception. However, none of them is applicable for all forms of color vision deficiencies and all image types. The manuscript proposes two image adaptation types that can be scaled and combined: type-based, increasing blue-yellow contrast, and severity-based adaptation that enhances red-green contrast. The quantitative, colorimetric evaluation confirmed that resulting images have an enhanced chromatic contrast, a larger color gamut, and additional image dominant colors compared to original images. The visual assessment involving ten color-deficient observers revealed that the degree of anomalous color perception (mild, moderate, or severe) and the type of image content (natural or artificial) influenced the image preference. The evaluation results demonstrated that the proposed image adaptations customized for the level of color vision anomaly outperformed the state-of-the-art daltonization focused on optimizing contrast for severe, dichromatic cases of deficiency. Furthermore, the color-deficient observers' choice of preference shifts from subtle color changes, in the case of natural scenes, to exaggerated yellow-blue contrast enhancement for infographics and data visualizations. The extracted conclusions suggest that a customized concept of image adaptation for the specific application and the specific color-deficient user is a better solution than existing methods that neglect the diversity of CVD forms and image types. [ABSTRACT FROM AUTHOR]