MTBWD: Multidirectional Two-Step Bisection Weighting Demosaicking for Image Sensors

This article proposes a multidirectional two-step bisection weighting demosaicking (MTBWD) method for the image sensors. For image demosaicking, complicated operations are typically employed to calculate more precise weights and reconstructed pixel values. Considering hardware implementation, we tend to avoid using complicated operations, such as multiplication; therefore, bisection weighting is proposed, implying that all interpolated weights are designed to be the fraction with a value of denominator that is a power of 2; however, if we use only the bisection weighting, it is challenging to adopt the multidirectional information. We, therefore, proposed two-step bisection weighting. In the first step, we compute the global directional information through the first bisection weighting of local directional information, consisting of variations and color difference values of cardinal and oblique directions. Then, the final color difference value is computed through the second-time bisection weighting of global directional information to interpolate the missing pixel. To reduce hardware cost, under the limitation of avoiding multiplication, MTBWD could still use multidirectional information to achieve competitive image quality. The very large-scale integration (VLSI) architecture of MTBWD is implemented and synthesized using TSMC 40-nm technology. Experimentally, compared with the related low-cost methods, the proposed MTBWD achieves the best average quality for diverse images, including images in Kodak24, IMAX, and DIV2K datasets and some photographs captured in a specific scene. The hardware reports confirm that the MTBWD is the most cost-effective in the current low-cost demosaicking studies with similar hardware costs.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-11-25
DOI
https://doi.org/10.1109/jsen.2024.3500005
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

MTBWD: Multidirectional Two-Step Bisection Weighting Demosaicking for Image Sensors

Kuan-Yu Huang, Cho-Yu Kuo, Yuan Sun, Chi-Ting Ni et al.
IEEE Sensors Journal
Image and Signal Denoising Methods
article

MTBWD: Multidirectional Two-Step Bisection Weighting Demosaicking for Image Sensors

Kuan-Yu Huang, Cho-Yu Kuo, Yuan Sun, Chi-Ting Ni, Pei‐Yin Chen, Hua Li, Han-Ping Shen
article en

Abstract

This article proposes a multidirectional two-step bisection weighting demosaicking (MTBWD) method for the image sensors. For image demosaicking, complicated operations are typically employed to calculate more precise weights and reconstructed pixel values. Considering hardware implementation, we tend to avoid using complicated operations, such as multiplication; therefore, bisection weighting is proposed, implying that all interpolated weights are designed to be the fraction with a value of denominator that is a power of 2; however, if we use only the bisection weighting, it is challenging to adopt the multidirectional information. We, therefore, proposed two-step bisection weighting. In the first step, we compute the global directional information through the first bisection weighting of local directional information, consisting of variations and color difference values of cardinal and oblique directions. Then, the final color difference value is computed through the second-time bisection weighting of global directional information to interpolate the missing pixel. To reduce hardware cost, under the limitation of avoiding multiplication, MTBWD could still use multidirectional information to achieve competitive image quality. The very large-scale integration (VLSI) architecture of MTBWD is implemented and synthesized using TSMC 40-nm technology. Experimentally, compared with the related low-cost methods, the proposed MTBWD achieves the best average quality for diverse images, including images in Kodak24, IMAX, and DIV2K datasets and some photographs captured in a specific scene. The hardware reports confirm that the MTBWD is the most cost-effective in the current low-cost demosaicking studies with similar hardware costs.

IEEE Sensors JournalVol. 25(3)
Focaltech Systems (Taiwan) (TW), MediaTek (Taiwan) (TW), National Kaohsiung University of Science and Technology (TW), National Cheng Kung University (TW)
National Science and Technology Council
Openalex Percentile: Top 79%
Image and Signal Denoising Methods
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