SRLab

Single image super resolution algorithm implementation (in progress)

Demo:

Source(128X128)

4X

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Requirement:

• Supported python version 2.7

• pip install Pillow

• pip install mock==1.0.1

• pip install six

• pip install -U numpy scipy scikit-learn

Example:

image = Image.open("test_data/babyface_4.png")

sr_image = SRImageFactory.create_sr_image(image)

reconstructed_sr_image = sr_image.reconstruct(2, 'iccv09')

reconstructed_sr_image.save("test_data/babyface_sr.png", "png")

Note:

Need to work more on performance, it will take around 20 seconds to reconstruct a 128*128 image to 2X its original size, and take around 1 minutes to 4X its original size.(On i7 Cpu, 8G ram)

Run the examples in example/sr_image_example.py:

Add root directory of SRLab to PYTHONPATH:

export PYTHONPATH=$PYTHONPATH:~/schen59/SRLab

Go to the example directory:

cd example

Run the example script:

python sr_image_example.py