{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T17:10:11Z","timestamp":1751389811253,"version":"3.41.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T00:00:00Z","timestamp":1747094400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T00:00:00Z","timestamp":1747094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Real-Time Image Proc"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s11554-025-01690-2","type":"journal-article","created":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T23:05:09Z","timestamp":1747091109000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An efficient single-stage ISP for smartphones using global context residual dense and residual channel attention modules"],"prefix":"10.1007","volume":"22","author":[{"given":"Roli","family":"Bansal","sequence":"first","affiliation":[]},{"given":"Anjali","family":"Pal","sequence":"additional","affiliation":[]},{"given":"Priti","family":"Sehgal","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,13]]},"reference":[{"key":"1690_CR1","doi-asserted-by":"publisher","DOI":"10.2307\/j.ctv1b0fvh1","volume-title":"The Global Smartphone: Beyond a Youth Technology","author":"D Miller","year":"2021","unstructured":"Miller, D., Rabho, L.A., Awondo, P., Vries, M., Duque, M., Garvey, P., Haapio-Kirk, L., Hawkins, C., Otaegui, A., Walton, S., Wang, X.: The Global Smartphone: Beyond a Youth Technology. ULC Press (2021)"},{"key":"1690_CR2","doi-asserted-by":"publisher","unstructured":"Rizzi, A., Gatta, C., Marini, D.: A new algorithm for unsupervised global and local color correction. Pattern Recognition Letters 24(11), 1663\u20131677 (2003) https:\/\/doi.org\/10.1016\/S0167-8655(02)00323-9 . Colour Image Processing and Analysis. First European Conference on Colour in Graphics, Imaging, and Vision (CGIV 2002)","DOI":"10.1016\/S0167-8655(02)00323-9"},{"key":"1690_CR3","doi-asserted-by":"publisher","unstructured":"Yuan, L., Sun, J.: Automatic exposure correction of consumer photographs. In: European Conference on Computer Vision (2012). https:\/\/doi.org\/10.1007\/978-3-642-33765-9_55","DOI":"10.1007\/978-3-642-33765-9_55"},{"key":"1690_CR4","doi-asserted-by":"publisher","unstructured":"Ignatov, A., Van\u00a0Gool, L., Timofte, R.: Replacing mobile camera isp with a single deep learning model. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2275\u20132285 (2020). https:\/\/doi.org\/10.1109\/CVPRW50498.2020.00276","DOI":"10.1109\/CVPRW50498.2020.00276"},{"key":"1690_CR5","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/978-3-030-67070-2_11","volume-title":"Computer Vision \u2013 ECCV 2020 Workshops","author":"L Dai","year":"2020","unstructured":"Dai, L., Liu, X., Li, C., Chen, J.: Awnet:aAttentive wavelet network for image isp. In: Bartoli, A., Fusiello, A. (eds.) Computer Vision \u2013 ECCV 2020 Workshops, pp. 185\u2013201. Springer, Cham (2020)"},{"key":"1690_CR6","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1007\/978-3-030-67070-2_12","volume-title":"Computer Vision - ECCV 2020 Workshops","author":"B-H Kim","year":"2020","unstructured":"Kim, B.-H., Song, J., Ye, J.C., Baek, J.: Pynet-ca: enhanced pynet with channel attention for end-to-end mobile image signal processing. In: Bartoli, A., Fusiello, A. (eds.) Computer Vision - ECCV 2020 Workshops, pp. 202\u2013212. Springer, Cham (2020)"},{"issue":"2","key":"1690_CR7","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1109\/TIP.2018.2872858","volume":"28","author":"E Schwartz","year":"2019","unstructured":"Schwartz, E., Giryes, R., Bronstein, A.M.: Deepisp: Toward learning an end-to-end image processing pipeline. IEEE Trans. Image Processing 28(2), 912\u2013923 (2019). https:\/\/doi.org\/10.1109\/TIP.2018.2872858","journal-title":"IEEE Trans. Image Processing"},{"key":"1690_CR8","doi-asserted-by":"publisher","unstructured":"Ignatov, A., Malivenko, G., al., R.T.: Pynet-v2 mobile: Efficient on-device photo processing with neural networks. In: 2022 26th International Conference on Pattern Recognition (ICPR), pp. 677\u2013684. IEEE Computer Society, Los Alamitos, CA, USA (2022). https:\/\/doi.org\/10.1109\/ICPR56361.2022.9956598","DOI":"10.1109\/ICPR56361.2022.9956598"},{"key":"1690_CR9","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Timofte, R., Zhang, Z., Liu, M., et.al.: AIM 2020 Challenge on Learned Image Signal Processing Pipeline (2020).","DOI":"10.1007\/978-3-030-67070-2_9"},{"key":"1690_CR10","doi-asserted-by":"publisher","unstructured":"Hsyu, M.-C., Liu, C.-W., Chen, C.-H., Chen, C.-W., Tsai, W.-C.: Csanet: High speed channel spatial attention network for mobile isp. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2486\u20132493 (2021). https:\/\/doi.org\/10.1109\/CVPRW53098.2021.00282","DOI":"10.1109\/CVPRW53098.2021.00282"},{"key":"1690_CR11","doi-asserted-by":"publisher","unstructured":"Zhang, H., Dai, Y., Li, H., Koniusz, P.: Deep stacked hierarchical multi-patch network for image deblurring. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5971\u20135979. IEEE Computer Society, Los Alamitos, CA, USA (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00613","DOI":"10.1109\/CVPR.2019.00613"},{"key":"1690_CR12","doi-asserted-by":"publisher","unstructured":"Mei, Y., Fan, Y., Zhou, Y.: Image super-resolution with non-local sparse attention. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3516\u20133525 (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.00352","DOI":"10.1109\/CVPR46437.2021.00352"},{"key":"1690_CR13","doi-asserted-by":"publisher","unstructured":"Lempitsky, V., Vedaldi, A., Ulyanov, D.: Deep image prior. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9446\u20139454 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00984","DOI":"10.1109\/CVPR.2018.00984"},{"key":"1690_CR14","doi-asserted-by":"publisher","unstructured":"Ratnasingam, S.: Deep camera: A fully convolutional neural network for image signal processing. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 3868\u20133878 (2019). https:\/\/doi.org\/10.1109\/ICCVW.2019.00480","DOI":"10.1109\/ICCVW.2019.00480"},{"key":"1690_CR15","doi-asserted-by":"publisher","unstructured":"Cheng, Y., Yue, H., Mao, Y.: A lightweight convolutional neural network for camera isp. In: 2021 IEEE 21st International Conference on Communication Technology (ICCT), pp. 1346\u20131350 (2021). https:\/\/doi.org\/10.1109\/ICCT52962.2021.9658007","DOI":"10.1109\/ICCT52962.2021.9658007"},{"key":"1690_CR16","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1007\/978-3-030-92659-5_21","volume-title":"Pattern Recognition","author":"P Chaudhari","year":"2021","unstructured":"Chaudhari, P., Schirrmacher, F., Maier, A., Riess, C., K\u00f6hler, T.: Merging-isp: Multi-exposure high dynamic range image signal processing. In: Bauckhage, C., Gall, J., Schwing, A. (eds.) Pattern Recognition, pp. 328\u2013342. Springer, Cham (2021)"},{"key":"1690_CR17","doi-asserted-by":"publisher","first-page":"2248","DOI":"10.1109\/TIP.2021.3051486","volume":"30","author":"Z Liang","year":"2021","unstructured":"Liang, Z., Cai, J., Cao, Z., Zhang, L.: Cameranet: a two-stage framework for effective camera isp learning. IEEE Trans. on Image Processing 30, 2248\u20132262 (2021). https:\/\/doi.org\/10.1109\/TIP.2021.3051486","journal-title":"IEEE Trans. on Image Processing"},{"key":"1690_CR18","doi-asserted-by":"publisher","unstructured":"Raimundo, D.W., Ignatov, A., Timofte, R.: Lan: Lightweight attention-based network for raw-to-rgb smartphone image processing. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 807\u2013815 (2022). https:\/\/doi.org\/10.1109\/CVPRW56347.2022.00096","DOI":"10.1109\/CVPRW56347.2022.00096"},{"key":"1690_CR19","doi-asserted-by":"publisher","unstructured":"Ignatov, A., Chiang, C.-M., al., K.: Learned smartphone isp on mobile npus with deep learning, mobile ai 2021 challenge: Report. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2503\u20132514 (2021). https:\/\/doi.org\/10.1109\/CVPRW53098.2021.00284","DOI":"10.1109\/CVPRW53098.2021.00284"},{"key":"1690_CR20","doi-asserted-by":"publisher","first-page":"74973","DOI":"10.1109\/ACCESS.2019.2921451","volume":"7","author":"P Liu","year":"2019","unstructured":"Liu, P., Zhang, H., Lian, W., Zuo, W.: Multi-level wavelet convolutional neural networks. IEEE Access 7, 74973\u201374985 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2921451","journal-title":"IEEE Access"},{"key":"1690_CR21","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Li, K., Li, K., Wang, L., Zhong, B., Fu, Y.: Image super-resolution using very deep residual channel attention networks. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 286\u2013301 (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_18","DOI":"10.1007\/978-3-030-01234-2_18"},{"key":"1690_CR22","doi-asserted-by":"publisher","unstructured":"Xing, Y., Li, C., Zhang, X., Chen, Q.: A well-aligned dataset for learning image signal processing on smartphones from a high-end camera. In: ACM SIGGRAPH 2022 Posters. SIGGRAPH \u201922. Association for Computing Machinery, New York, NY, USA (2022). https:\/\/doi.org\/10.1145\/3532719.3543252","DOI":"10.1145\/3532719.3543252"},{"issue":"2","key":"1690_CR23","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91\u2013110 (2004). https:\/\/doi.org\/10.1023\/B:VISI.0000029664.99615.94","journal-title":"Int. J. Comput. Vision"},{"key":"1690_CR24","doi-asserted-by":"publisher","unstructured":"Vedaldi, A., Fulkerson, B.: Vlfeat: An open and portable library of computer vision algorithms. In: Proceedings of the 18th ACM International Conference on Multimedia. MM \u201910, pp. 1469\u20131472. Association for Computing Machinery, New York, NY, USA (2010). https:\/\/doi.org\/10.1145\/1873951.1874249","DOI":"10.1145\/1873951.1874249"},{"key":"1690_CR25","doi-asserted-by":"publisher","unstructured":"Sun, D., Yang, X., Liu, M., Kautz, J.: Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8934\u20138943. IEEE Computer Society, Los Alamitos, CA, USA (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00931","DOI":"10.1109\/CVPR.2018.00931"},{"key":"1690_CR26","doi-asserted-by":"publisher","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00745","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1690_CR27","doi-asserted-by":"publisher","unstructured":"Peng, C., Zhang, X., Yu, G., Luo, G., Sun, J.: Large kernel matters\u2013improve semantic segmentation by global convolutional network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4353\u20134361 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.189","DOI":"10.1109\/CVPR.2017.189"},{"key":"1690_CR28","doi-asserted-by":"publisher","unstructured":"Li, X., Wang, W., Hu, X., Yang, J.: Selective kernel networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 510\u2013519 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00060","DOI":"10.1109\/CVPR.2019.00060"},{"key":"1690_CR29","doi-asserted-by":"publisher","unstructured":"Basak, H., Kundu, R., Agarwal, A., Giri, S.: Single image super-resolution using residual channel attention network. In: 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS), pp. 219\u2013224 (2020). https:\/\/doi.org\/10.1109\/ICIIS51140.2020.9342688","DOI":"10.1109\/ICIIS51140.2020.9342688"},{"key":"1690_CR30","doi-asserted-by":"publisher","unstructured":"Charbonnier, P., Blanc-Feraud, L., Aubert, G., Barlaud, M.: Two deterministic half-quadratic regularization algorithms for computed imaging. In: Proceedings of 1st International Conference on Image Processing, vol. 2, pp. 168\u20131722 (1994). https:\/\/doi.org\/10.1109\/ICIP.1994.413553","DOI":"10.1109\/ICIP.1994.413553"},{"issue":"1","key":"1690_CR31","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/S0262-8856(96)01112-2","volume":"15","author":"Z Zhang","year":"1997","unstructured":"Zhang, Z.: Parameter estimation techniques: a tutorial with application to conic fitting. Image Vision Comput. 15(1), 59\u201376 (1997). https:\/\/doi.org\/10.1016\/S0262-8856(96)01112-2","journal-title":"Image Vision Comput."},{"key":"1690_CR32","unstructured":"Wu, B., Duan, H., Liu, Z., Sun, G.: Srpgan: Perceptual generative adversarial network for single image super resolution. ArXiv abs\/1712.05927 (2017)"},{"issue":"11","key":"1690_CR33","doi-asserted-by":"publisher","first-page":"1680","DOI":"10.1109\/LSP.2018.2871419","volume":"25","author":"JM Martin-Do\u00f1as","year":"2018","unstructured":"Martin-Do\u00f1as, J.M., Gomez, A.M., Gonzalez, J.A., Peinado, A.M.: A deep learning loss function based on the perceptual evaluation of the speech quality. IEEE Signal Processing Lett. 25(11), 1680\u20131684 (2018). https:\/\/doi.org\/10.1109\/LSP.2018.2871419","journal-title":"IEEE Signal Processing Lett."},{"key":"1690_CR34","doi-asserted-by":"publisher","unstructured":"Lin, T., Goyal, P., Girshick, R., He, K., Dollar, P.: Focal loss for dense object detection. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2999\u20133007. IEEE Computer Society, Los Alamitos, CA, USA (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.324","DOI":"10.1109\/ICCV.2017.324"},{"key":"1690_CR35","doi-asserted-by":"publisher","first-page":"2072","DOI":"10.1109\/TIP.2021.3050850","volume":"30","author":"W Yang","year":"2021","unstructured":"Yang, W., Wang, W., Huang, H., Wang, S., Liu, J.: Sparse gradient regularized deep retinex network for robust low-light image enhancement. IEEE Trans. Image Process. 30, 2072\u20132086 (2021). https:\/\/doi.org\/10.1109\/TIP.2021.3050850","journal-title":"IEEE Trans. Image Process."}],"container-title":["Journal of Real-Time Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-025-01690-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11554-025-01690-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-025-01690-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T16:53:12Z","timestamp":1751388792000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11554-025-01690-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,13]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["1690"],"URL":"https:\/\/doi.org\/10.1007\/s11554-025-01690-2","relation":{},"ISSN":["1861-8200","1861-8219"],"issn-type":[{"type":"print","value":"1861-8200"},{"type":"electronic","value":"1861-8219"}],"subject":[],"published":{"date-parts":[[2025,5,13]]},"assertion":[{"value":"4 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"110"}}