GitHub / UgurCan222 / A-Different-Approach--Image-Enhancement-with-Imputation-and-Regression-Methods
This experimental work presents a different approach to increase the size and quality of an image by adding a blank pixel around each pixel in an image, enlarging the image, breaking it into parts, and generating these blank pixels by predicting them with models.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UgurCan222%2FA-Different-Approach--Image-Enhancement-with-Imputation-and-Regression-Methods
PURL: pkg:github/UgurCan222/A-Different-Approach--Image-Enhancement-with-Imputation-and-Regression-Methods
Stars: 0
Forks: 0
Open issues: 0
License: mit
Language: Python
Size: 1.8 MB
Dependencies parsed at: Pending
Created at: 10 months ago
Updated at: 10 months ago
Pushed at: 10 months ago
Last synced at: 3 months ago
Topics: ai-image-upscaling, computer-vision, digital-image-processing, gradient-boosting, image-analysis, image-enhancement, image-enlargement, image-interpolation, image-processing, imputation, knn, machine-learning, numpy, opencv, pixel-prediction, python, randomforest, regression-models, super-resolution, xgboost