1 citations · 1 across the 2 of their papers we have counts for
6 papers
Attention on Classification for Fire Segmentation
Milad Niknejad, Alexandre Bernardino
Detection and localization of fire in images and videos are important in tackling fire incidents. Although semantic segmentation methods can be used to indicate the location of pix…
Image Restoration Using Conditional Random Fields and Scale Mixtures of Gaussians
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper proposes a general framework for internal patch-based image restoration based on Conditional Random Fields (CRF). Unlike related models based on Markov Random Fields (MR…
External Patch-Based Image Restoration Using Importance Sampling
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper introduces a new approach to patch-based image restoration based on external datasets and importance sampling. The Minimum Mean Squared Error (MMSE) estimate of the imag…
Poisson Image Denoising Using Best Linear Prediction: A Post-processing Framework
Milad Niknejad, Mario A. T. Figueiredo
In this paper, we address the problem of denoising images degraded by Poisson noise. We propose a new patch-based approach based on best linear prediction to estimate the underlyin…
Class-specific image denoising using importance sampling
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
In this paper, we propose a new image denoising method, tailored to specific classes of images, assuming that a dataset of clean images of the same class is available. Similarly to…
Class-specific Poisson denoising by patch-based importance sampling
Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
In this paper, we address the problem of recovering images degraded by Poisson noise, where the image is known to belong to a specific class. In the proposed method, a dataset of c…