arXiv:2504.07758v1 Announce Type: new Abstract: Polarization cameras can capture multiple polarized images with different polarizer angles in a single shot, bringing convenience to polarization-based downstream tasks. However, their direct outputs are color-polarization filter array (CPFA) raw images, requiring demosaicing to reconstruct full-resolution, full-color polarized images; unfortunately, this necessary step introduces artifacts that make polarization-related parameters such as the degree of polarization (DoP) and angle of polarization (AoP) prone to error. Besides, limited by the hardware design, the resolution of a polarization camera is often much lower than that of a conventional RGB camera. Existing polarized image demosaicing (PID) methods are limited in that they cannot enhance resolution, while polarized image super-resolution (PISR) methods, though designed to obtain high-resolution (HR) polarized images from the demosaicing results, tend to retain or even amplify errors in the DoP and AoP introduced by demosaicing artifacts. In this paper, we propose PIDSR, a joint framework that performs complementary Polarized Image Demosaicing and Super-Resolution, showing the ability to robustly obtain high-quality HR polarized images with more accurate DoP and AoP from a CPFA raw image in a direct manner. Experiments show our PIDSR not only achieves state-of-the-art performance on both synthetic and real data, but also facilitates downstream tasks.
The article “PIDSR: Polarized Image Demosaicing and Super-Resolution” addresses the challenges associated with polarization cameras and their outputs, known as color-polarization filter array (CPFA) raw images. These raw images require demosaicing to reconstruct full-resolution, full-color polarized images, but this step introduces artifacts that can lead to errors in polarization-related parameters such as the degree of polarization (DoP) and angle of polarization (AoP). Additionally, polarization cameras often have lower resolution compared to conventional RGB cameras. Existing methods for polarized image demosaicing (PID) cannot enhance resolution, and polarized image super-resolution (PISR) methods tend to amplify errors introduced by demosaicing artifacts. To overcome these limitations, the authors propose PIDSR, a joint framework that performs complementary polarized image demosaicing and super-resolution. The results demonstrate that PIDSR can obtain high-quality, high-resolution polarized images with more accurate DoP and AoP, showcasing its potential for improving downstream tasks.
The Power of PIDSR: Enhancing Polarized Images with Higher Resolution and Accuracy
Polarization cameras have revolutionized the field of imaging by allowing the capture of multiple polarized images in a single shot. This advancement brings convenience to polarization-based downstream tasks, opening up new possibilities for applications in various fields. However, despite their advantages, polarization cameras present certain challenges that need to be addressed.
The direct outputs of polarization cameras are color-polarization filter array (CPFA) raw images. To reconstruct full-resolution, full-color polarized images, a demosaicing process is required. Unfortunately, this necessary step introduces artifacts that can lead to errors in polarization-related parameters such as the degree of polarization (DoP) and angle of polarization (AoP).
Moreover, the resolution of polarization cameras is often lower than that of conventional RGB cameras due to hardware limitations. Existing polarized image demosaicing (PID) methods are unable to enhance resolution, and polarized image super-resolution (PISR) methods tend to amplify errors introduced by demosaicing artifacts.
In response to these challenges, we propose a novel joint framework called PIDSR (Polarized Image Demosaicing and Super-Resolution). Our framework aims to obtain high-quality, high-resolution polarized images with more accurate DoP and AoP from CPFA raw images in a direct manner.
In our proposed approach, PIDSR combines the processes of polarized image demosaicing and super-resolution. By integrating these two tasks, we are able to leverage their complementary nature and overcome the limitations of existing methods.
The results of our experiments show that PIDSR achieves state-of-the-art performance on both synthetic and real data. Not only does it provide enhanced resolution, but it also significantly improves the accuracy of the DoP and AoP parameters. This breakthrough not only benefits standalone polarized image applications but also facilitates downstream tasks that rely on precise polarization information.
Benefits of PIDSR:
- Obtains high-resolution polarized images from CPFA raw images
- Improves accuracy of polarization-related parameters (DoP and AoP)
- Reduces artifacts introduced by demosaicing process
- Enhances performance on both synthetic and real data
- Enables more robust downstream tasks reliant on polarization information
The potential applications of PIDSR are vast and diverse. Fields such as medical imaging, remote sensing, and computer vision can benefit from the enhanced capabilities provided by this framework. For example, in medical imaging, PIDSR can offer improved accuracy in polarization-based diagnostics or surgical procedures. Additionally, in remote sensing applications, PIDSR can enhance the quality and resolution of polarized image data for improved analysis and interpretation.
To unlock the full potential of polarization cameras, the development of advanced processing techniques is crucial. Our PIDSR framework represents a significant step forward in the field, offering a comprehensive solution to enhance polarized images with both higher resolution and accuracy. With further research and refinement, PIDSR has the potential to revolutionize various industries and drive innovation in polarization-based imaging.
The paper introduces a new framework called PIDSR (Polarized Image Demosaicing and Super-Resolution) that tackles the challenges faced by polarization cameras in capturing and reconstructing full-resolution, full-color polarized images. These cameras capture multiple polarized images with different polarizer angles in a single shot, but their direct outputs are color-polarization filter array (CPFA) raw images, which require demosaicing to reconstruct the final images. Unfortunately, demosaicing introduces artifacts that can lead to errors in polarization-related parameters such as the degree of polarization (DoP) and angle of polarization (AoP).
Moreover, polarization cameras often have lower resolutions compared to conventional RGB cameras due to hardware limitations. Existing demosaicing methods for polarized images are unable to enhance resolution, and polarized image super-resolution (PISR) methods, which aim to obtain high-resolution polarized images from demosaiced results, tend to retain or even amplify errors introduced by demosaicing artifacts.
In this context, PIDSR offers a joint framework that addresses both demosaicing and super-resolution, enabling the direct and robust generation of high-quality, high-resolution polarized images with more accurate DoP and AoP. The proposed framework not only achieves state-of-the-art performance on both synthetic and real data, but also facilitates downstream tasks that rely on polarized image analysis.
This research is significant as it addresses key limitations in polarization camera technology and provides a comprehensive solution for enhancing the quality and resolution of polarized images. By improving the accuracy of polarization-related parameters, PIDSR opens up possibilities for various applications, including object detection, material classification, and scene understanding. Future directions could involve further optimizing the framework for real-time processing and exploring its potential in specific domains, such as medical imaging or autonomous driving. Additionally, investigating the combination of PIDSR with other advanced image processing techniques, such as denoising or image fusion, could lead to further improvements in the quality and utility of polarized images.
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