4 papers
A Subjective Study on a New Sharpness Informed Class of Metrics
Uditangshu Aurangabadkar, Vibhoothi Vibhoothi, Darren Ramsook +1
Perceptual loss functions in Deep Neural Network (DNN) deblurring architectures improve the overall quality of restored images. However, few focus on explicitly targeting sharpness…
Impact of a Sharpness Based Loss Function for Removing Out-of-Focus Blur
Uditangshu Aurangabadkar, Darren Ramsook, Anil Kokaram
Recent research has explored complex loss functions for deblurring. In this work, we explore the impact of a previously introduced loss function - Q which explicitly addresses shar…
A Sharpness Based Loss Function for Removing Out-of-Focus Blur
Uditangshu Aurangabadkar, Darren Ramsook, Anil Kokaram
The success of modern Deep Neural Network (DNN) approaches can be attributed to the use of complex optimization criteria beyond standard losses such as mean absolute error (MAE) or…
A Dictionary Based Approach for Removing Out-of-Focus Blur
Uditangshu Aurangabadkar, Anil Kokaram
The field of image deblurring has seen tremendous progress with the rise of deep learning models. These models, albeit efficient, are computationally expensive and energy consuming…