Imaging Principle and Image Quality Enhancement Technology of Mobile Phone Camera Modules
DOI:
https://doi.org/10.61173/stecep16272Keywords:
Smartphone imaging, CMOS image sensor, image signal processing (ISP), computational imaging, HDR processingAbstract
Mini optical components are used in Smart phone image forming system. Complementary metal-oxide-semiconductor (CMOS) digital-analog converting components and an image signal processor (ISP) have computational image-forming algorithms to convert the light to digital images. The optical path is composed of a lens group, aperture, IR-cut filter, microlens array, color filtering arrays, and photodiode. The incident photos are converted to electric signals and then processed by digital processes. ISP performs several image processing operations such as black level rectification, noise removal, high-dynamic-range (HDR), and white balance adjusting then the images will be encoded and stored. Miniaturization of optical systems puts limits on the collection of photons, the dynamic range, and the optical performance, which has led to the use of backlighting, Quad Bayer pixel architecture, multi-camera systems, and periscope optics. These hardware limitations are overcome by multi-image alignment, HDR fusion, burst denoising, and image restoration in the computational imaging process. From the photon capture to the creation of a digital image, this article discusses the imaging process and its relation to optical design, sensor architecture, ISP, and computational algorithms to evaluate the quality of the images created by the modern smartphone cameras.
References
Sun W-S, Liu Y-H, Tien C-L. Optical Design of a Miniaturized 10× Periscope Zoom Lens for Smartphones. Micromachines, 2023, 14(6): 1272. https://doi.org/10.3390/mi14061272.
Ignatov A, Van Gool L, Timofte R. Replacing Mobile Camera ISP with a Single Deep Learning Model. IEEE, 2020. https://doi.org/10.1109/CVPRW50498.2020.00276.
Diamond S, Sitzmann V, Julca-Aguilar F D, et al. Dirty Pixels: Towards End-to-end Image Processing and Perception. ACM Transactions on Graphics (TOG), 2021. https://doi.org/10.1145/3446918.
Li J, Aggarwal N, Gudemann L, et al. The Need for Neural ISP in the Small-Pixel Era: How Shrinking Pixels Push Optics to the Limit and Neural Restoration Pushes Back. arXiv:2606.07675, 2026. https://doi.org/10.48550/arXiv.2606.07675.
Afifi Mahmoud, Zhang Ran, Brown M S. Raw-JPEG Adapter: Efficient Raw Image Compression with JPEG. arXiv:2509.19624, 2025. https://doi.org/10.48550/arXiv.2509.19624.
Luo A, Fujii D, Nonaka K, et al. Storage-and-Memory-Efficient Learned Image Compression With Quality-Aware Hyperprior Pruning. IET Image Processing, 2025, 19 (15): 3251-3264.
Blahnik Vladan, Schindelbeck Oliver. Smartphone imaging technology and its applications. 2021, 10(3): 145-232.
Hasinoff S W, Sharlet D, Geiss R, et al. Burst photography for high dynamic range and low-light imaging on mobile cameras. ACM Transactions on Graphics (TOG), 2016, 35(6cd): 192. https://doi.org/10.1145/2980179.2980254.
Venkataraman K, Lelescu D, Duparré J, et al. PiCam: an ultra-thin high performance monolithic camera array. ACM Transactions on Graphics (TOG), 2013, 32(6): 1-13. https://doi.org/10.1145/2508363.2508390.
Wronski B, Garcia-Dorado I, Ernst M, et al. Handheld multi-frame super-resolution. ACM Transactions on Graphics, 2019, 38(4): 1-18. https://doi.org/10.1145/3306346.3323024.
Delbracio M, Sapiro G. Burst Deblurring: Removing Camera Shake Through Fourier Burst Accumulation. IEEE, 2015. https://doi.org/10.1109/CVPR.2015.7298852.
Tabellion E, Karnad N, Glaser N, et al. Computational long exposure mobile photography. ACM Transactions on Graphics, 2023, 42(4): 1-15. https://doi.org/10.1145/359212.
Godard C, Matzen K, Uyttendaele M. Deep burst denoising. arXiv preprint arXiv:1712.05790, 2027. https://doi.org/10.48550/arXiv.1712.05790.
Xing Yazhou, Li Changlin, Zhang Xuaner, et al. A well-aligned dataset for learning image signal processing on smartphones from a high-end camera. In Proceedings of the 19th ACM International Conference on Computing Frontiers, 2022, 45: 1-2. https://doi.org/10.1145/3532719.35432.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 by the authors.
This work is licensed under a Creative Commons Attribution 4.0 International License.
