VISUAL IMAGE PROCESSING LABORATORY
A research project on computational vision science.

Funded by Generalitat Valenciana under grant AICO-2020-136 (VIPLab) and CIAICO/2022/051 (IMaLeVICS) 

RESOURCES

Codes

  • Amiri, M.M., Garcia-Nieto, S., Morillas, S. and Fairchild, M.D., «Spectral reflectance reconstruction using fuzzy logic system training: Color science application«, Sensors (Switzerland), 2020, 20(17), pp. 1–18, 4726 SENSORS 2020
  • Latorre-Carmona, P., Miñana, J.-J. and Morillas, S. «Colour image denoising by eigenvector analysis of neighbourhood colour samples«, Signal, Image and Video Processingthis link is disabled, 2020, 14(3), pp. 483–490 SIVP2020 
  • J. Prats-Climent, L. Gómez-Robledo, R. Huertas, S. García-Nieto, M.J. Rodríguez-Álvarez and S. Morillas, «A study of neural network-based LCD display characterization«, London Imaging Meeting 2021.
  • S. Morillas,P. Latorre-Carmona,R. Huertas and M. Pedersen, «Using STRESS to compute the agreement between computed image quality measures and observer scores: advantanges and open issues«, Mathematical Modelling in Engineering & Human Behaviour 2021.
  • S. Morillas, L. Gómez-Robledo, R. Huertas and M.Melgosa «Method to determine the degrees of consistency in experimental datasets of perceptual color differences» JOSA2016
  • Reza Ghasemi, Samuel Morillas, Ahmad Nezakati and Mohammadreza Rabiei «Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers» BCFM Code
  • P. Latorre-Carmona, R. Huertas, M. Pedersen, S. Morillas «Proposal of  a new fidelity measure between computed image quality and observers  quality scores accounting for scores variability» JVIS 2022 Code
  • K. Almutairi, S. Morillas, P. Latorre-Carmona «Fuzzy Inference Systems to Fine-Tune a Local Eigenvector Image Smoothing Method» FuzzyEIG 2024

Data

  • J. Prats-Climent, L. Gómez-Robledo, R. Huertas, S. García-Nieto, M.J. Rodríguez-Álvarez, S. Morillas, «A study of neural network-based LCD display characterization«, London Imaging Meeting 2021.

Papers and documentation