Chang J.-MJIAN-JIUN DING2021-09-022021-09-022020https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098462889&doi=10.1109%2fICCE-Taiwan49838.2020.9258256&partnerID=40&md5=9066c87a494a1d744e8482bdcc1ee133https://scholars.lib.ntu.edu.tw/handle/123456789/580964Lossless image compression consists of two processes, pixel prediction and residue encoding. Recently, deep neural network (DNN) has been widely adopted in signal prediction. In this work, we apply a DNN architecture together with the information of surrounding pixels weighted by their similarities for pixel prediction. Simulations show that, with the proposed algorithm, the pixels can be predicted more precisely, which is very helpful for lossless image compression. ? 2020 IEEE.Deep neural networks; Forecasting; Image compression; Pixels; Regression analysis; Lossless image compression; Prediction techniques; Ridge regression; Signal prediction; Neural networksDeep Neural Network and Weighted Ridge Regression Based Pixel Prediction Techniqueconference paper10.1109/ICCE-Taiwan49838.2020.92582562-s2.0-85098462889