Image recoloring for Red-Green dichromats with compensation range-based naturalness preservation and refined dichromacy gamut

Huang, Wangkang; Zhu, Zhenyang; Chen, Ligeng; Go, Kentaro; Chen, Xiao-Diao; Mao, Xiaoyang

doi:10.1007/s00371-022-02549-4

Cited by 5 publications

(22 citation statements)

References 19 publications

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“…6 and Fig. 7 show examples of compensation results for different degrees of the protan and deutan defects using existing methods [14,34] and the proposed method, respectively. In Fig.…”

Section: Discussionmentioning

confidence: 99%

“…making it difficult to identify details. In response, the image recolored using Huang et al's [14] (Fig. 6(c)) and Zhu et al's method [34] (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…Recolored images produced by [14,34] enhanced the contrast between the flower and leaves and increased the brightness of the flower well; however, the leaves were recolored bluish in [34], that is, naturalness was not well preserved. Although Huang's method [14] performs well at high degree of CVD, it suffers from significant losses in naturalness at medium and low degrees of CVD. The image result from the proposed method (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, a compensation range calculation formula similar to that in [14] is introduced. Initially, we calculate the loss radius R i for color c i based on Eq.…”

Section: Compensation Rangementioning

confidence: 99%

“…Huang et al [14] proposed an image-recoloring method for red-green dichromacy compensation. Because the CVD color gamut modeled by Machado et al [23] is defined in the RGB color space, Huang et al [14] remapped the gamut from the RGB space to the Lab space. Then, a curved surface passing through the L*axis of the Lab space was fitted using the least squares method.…”

Section: Introductionmentioning

confidence: 99%

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Fast Image Recoloring for Red-Green Anomalous Trichromacy with Contrast Enhancement and Naturalness Preservation

Zhou,

Huang,

Zhu

et al. 2024

Preprint

Self Cite

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Color vision deficiency (CVD) is an eye disease caused by genetics that reduces the ability to distinguish colors, affecting approximately 200 million people worldwide. In response, image recoloring approaches have been proposed in existing studies for CVD compensation, and a state-of-the-art recoloring algorithm has even been adapted to offer personalized CVD compensation; however, it is built on a color space that is lacking perceptual uniformity, and its low computation efficiency hinders its usage in daily life by individuals with CVD. In this paper, we propose a fast and personalized degree-adaptive image-recoloring algorithm for CVD compensation that considers naturalness preservation and contrast enhancement. Moreover, we transferred the simulated color gamut of the varying degrees of CVD in RGB color space to CIE L*a*b* color space, which offers perceptual uniformity. To verify the effectiveness of our method, we conducted quantitative and subject evaluation experiments, demonstrating that our method achieved the best scores for contrast enhancement and naturalness preservation.

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“…6 and Fig. 7 show examples of compensation results for different degrees of the protan and deutan defects using existing methods [14,34] and the proposed method, respectively. In Fig.…”

Section: Discussionmentioning

confidence: 99%

“…making it difficult to identify details. In response, the image recolored using Huang et al's [14] (Fig. 6(c)) and Zhu et al's method [34] (Fig.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…In this study, a compensation range calculation formula similar to that in [14] is introduced. Initially, we calculate the loss radius R i for color c i based on Eq.…”

Section: Compensation Rangementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fast Image Recoloring for Red-Green Anomalous Trichromacy with Contrast Enhancement and Naturalness Preservation

Zhou,

Huang,

Zhu

et al. 2024

Preprint

Self Cite

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show abstract

Fast image recoloring for red–green anomalous trichromacy with contrast enhancement and naturalness preservation

Zhou,

Huang,

Zhu

et al. 2024

Vis Comput

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Image recoloring for color vision deficiency compensation using Swin transformer

Chen,

Zhu,

Huang

et al. 2024

Neural Comput & Applic

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People with color vision deficiency (CVD) have difficulty in distinguishing differences between colors. To compensate for the loss of color contrast experienced by CVD individuals, a lot of image recoloring approaches have been proposed. However, the state-of-the-art methods suffer from the failures of simultaneously enhancing color contrast and preserving naturalness of colors [without reducing the Quality of Vision (QOV)], high computational cost, etc. In this paper, we propose an image recoloring method using deep neural network, whose loss function takes into consideration the naturalness and contrast, and the network is trained in an unsupervised manner. Moreover, Swin transformer layer, which has long-range dependency mechanism, is adopted in the proposed method. At the same time, a dataset, which contains confusing color pairs to CVD individuals, is newly collected in this study. To evaluate the performance of the proposed method, quantitative and subjective experiments have been conducted. The experimental results showed that the proposed method is competitive to the state-of-the-art methods in contrast enhancement and naturalness preservation and has a real-time advantage. The code and model will be made available at https://github.com/Ligeng-c/CVD_swin.

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Image recoloring for Red-Green dichromats with compensation range-based naturalness preservation and refined dichromacy gamut

Cited by 5 publications

References 19 publications

Fast Image Recoloring for Red-Green Anomalous Trichromacy with Contrast Enhancement and Naturalness Preservation

Fast Image Recoloring for Red-Green Anomalous Trichromacy with Contrast Enhancement and Naturalness Preservation

Fast image recoloring for red–green anomalous trichromacy with contrast enhancement and naturalness preservation

Image recoloring for color vision deficiency compensation using Swin transformer

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