super-resolution reconstruction

Feature Description

Super-resolution reconstruction refers to the process of converting low-resolution images into high-resolution images using super-resolution technology. The core principle of super-resolution reconstruction based on deep learning is to train deep neural networks to learn the mapping relationship between low-resolution images and high-resolution images, thereby predicting and supplementing missing details, and improving image clarity, sharpness, and texture representation.

The input source data is low-resolution imagery, and the output result is the corresponding high-resolution imagery. The super-resolution scaling factor is determined by the input model file. For example, for an image with dimensions of 10000×10000, after running a 2x super-resolution model, you will obtain an image with dimensions of 20000×20000; after running a 4x super-resolution model, you will obtain an image with dimensions of 40000×40000.

Parameter description

Parameter Name parameter interpretation parameter type
file type Select whether the file type is a dataset or a folder. String
Data Source The file database that stores the image dataset. String
Dataset Select an image dataset or mosaic dataset. DatasetVector
file path Select the folder path; it will automatically read the image files within. Supports five image types: tif, tiff, img, png, jpg, including their uppercase forms. DatasetVector
model file Specify the model file (*.sdm) used for super-resolution reconstruction. String
Batch Size The number of images processed in a single step during training. Appropriately increasing the batch size can improve interpretation efficiency, but it is limited by the GPU memory (for GPU inference) or system memory (for CPU inference) size. Integer
Processor Type Specify the processor type. String
GPU ID Specify the GPU identifier for processing data, default is GPU. String
result save path Specify the folder path for saving results. String
Result File Name Specify the result file name. If the source data file type is "folder", the result file name will be appended with "_" to the original image file names to distinguish the super-resolution reconstruction results of multiple images. String

Output Result

Parameter Name parameter interpretation parameter type
super-resolution reconstruction result If the source data file type is "dataset", the output image format will be tif; if the source data file type is "folder", the output image format will remain consistent with the original image files. String