Real-time rolling shutter compensation for a complementary metal-oxide semiconductor image sensor

Lee, Yun Gu

doi:10.1117/1.oe.57.10.100501

Cited by 3 publications

(4 citation statements)

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“…Many algorithms have been developed to compensate the geometric distortion from the rolling shutter effect and stabilize the shaky video [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. A simple two-dimensional model was proposed to remove perceived camera motion [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…Dong [ 18 ] hence proposed fast video stabilization for strict real-time applications and dramatically reduced the processing complexity. However, it is not still suitable for use with real-time mobile applications [ 19 ]. To further reduce the processing time, real-time method for a CMOS image sensor was proposed [ 2 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, it is not still suitable for use with real-time mobile applications [ 19 ]. To further reduce the processing time, real-time method for a CMOS image sensor was proposed [ 2 , 19 ]. Its computational complexity is extremely low enough to run it on CPUs in from middle-end to high-end mobile devices.…”

Section: Introductionmentioning

confidence: 99%

“…There are two major concerns in implementing the algorithm using hardware: hardware complexity increase and additional memory access. The hardware complexity may be significantly reduced by adopting fast algorithms such as [ 2 , 19 ]. However, VSRSC requires very large additional memory access, which is a huge burden in real-time devices, especially for low-end.…”

Section: Introductionmentioning

confidence: 99%

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Low Memory Access Video Stabilization for Low-Cost Camera SoC

Lee

2022

Sensors

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Video stabilization is one of the most important features in consumer cameras. Even simple video stabilization algorithms may need to access the frames several times to generate a stabilized output image, which places a significant burden on the camera hardware. This high-memory-access requirement makes it difficult to implement video stabilization in real time on low-cost camera SoC. Reduction of the memory usage is a critical issue in camera hardware. This paper presents a structure and layout method to efficiently implement video stabilization for low-end hardware devices in terms of shared memory access amount. The proposed method places sub-components of video stabilization in a parasitic form in other processing blocks, and the sub-components reuse data read from other processing blocks without directly accessing data in the shared memory. Although the proposed method is not superior to the state-of-the-art methods applied in post-processing in terms of video quality, it provides sufficient performance to lower the cost of camera hardware for the development of real-time devices. According to my analysis, the proposed one reduces the memory access amount by 21.1 times compared to the straightforward method.

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