I am a Master’s student, currently conducting research on turtle‘s camouflage. I recently reviewed a portion of the literature on JND using MICA Toolbox and QCPA to calculate goals and backgrounds. However, I have encountered some uncertainties regarding the correct procedure for calculating JNDs and would deeply appreciate your guidance.
Based on my understanding, I have outlined the following steps:
- Obtain cone-catch images. In my experiments, I am using human and ferret vision models.
- Run the QCPA framework with Gaussian Acuity Control.
- On the acuity-controlled images, execute “Pattern Colour and Luminance Measurements” under “Image Analysis.”
- Using the data obtained from step 3, select “Color JND Difference Calculator” and “Luminance JND Difference Calculator” under “Data Analysis” to compute CJND and LJND.
Could you kindly confirm if this method is correct? If there are any inaccuracies, I would be extremely grateful if you could share your approach to calculating JNDs.
Additionally, I have experienced considerable processing times while running the QCPA framework, even after cropping the images to focus on the most relevant areas. Have you encountered similar issues? Could the large size of the images be a contributing factor?
Thank you very much for your time and assistance. I truly appreciate your help and look forward to your response. :^)
Hi,
In essence the proposed workflow is correct, however, to calculate delta S values between areas or pixels it is not necessary to apply acuity controls, albeit possible and depending on your aim to include additional elements of the receiver.
Indeed, the bigger the picture, the longer processing takes. Please take caution when cropping the image, I would recommend working with ROIs rather than cropping.
Cheers,
Cedric