PicTechs

Jovianizer

High-Level Project Summary

The idea of our solution is a python application that includes wide range of features that manipulates raw images according to what the image needs to be more descriptive, these features include contrast enhancement, brightness adjustment, noise removal, striped images enhancer, different masks and filters such as Gaussian and Laplacian, grey scale slicing and grey level resolution, histogram equalization and the negative image of the inputted image. The application also provides the user with the capability to share the processed images via social media platforms and create artistic images from NASA’s images and processed images to provide the public with scientific and artistic experiment.

Link to Final Project

https://github.com/Maryam-Sheriff/Space-Apps2022

Link to Project "Demo"

https://drive.google.com/drive/u/0/folders/10ixgXCIQX5oT1Mskrg1OhgJdhu2pCurB

Detailed Project Description

The project is a python-based desktop application that’s composed of 2 perspectives: the user perspective which is the UI (User interface) and the developer perspective which is the backend of the desktop application.

The user perspective which is the UI of the application is a galactic themed user interface inspired by the Jovian system (Jupiter and its moons), the shapes of the moons represent the icons which access each feature in the application, also the UI is super user-friendly and provides a unique experiment for the public to explore the Jovian system in the most facilitated way as it shows the raw image side by side to the processed image and its histogram configuration in addition to list of different operations selected by the user.

The backend perspective is a python programmed functions-oriented code that call specific function depending on the selected feature by the user.

The functions provided include:

1. Brightness adjustment that’s done by increasing or decreasing the brightness level of the image using a slider.

2. Arithmetic operations which composed of adding 2 images, subtracting 2 images, multiplying 2 images, and dividing 2 images.

3. Histogram equalization that’s used to improve contrast in images as it accomplishes this by effectively spreading out the most frequent intensity values, i.e., stretching out the intensity range of the image.

4. Median filter that works on noise removal with preservation of edges.

5. Mean filter that helps in smoothing images and reducing the amount of intensity variation between one pixel and the next. It is often used toreduce noise in images.

6. Gaussian filter that’s used in reducing the size of an image. When down sampling an image, it is common to apply a low-pass filter to the image prior to resampling. This is to ensure that spurious high-frequency information does not appear in the down sampled image (aliasing), also used in blurring and removing specific details and noise.

7. Bit plane slicing which is used in representing an image with one or more bits of the byte used for each pixel. One can use only MSB to represent the pixel, which reduces the original gray level to a binary image. The three main goals of bit plane slicing are: converting a gray level image to a binary image.

8. Thresholding that’s used in converting an image from color or grayscale into a binary image, i.e., one that is simply black and white. Most frequently, we use thresholding as a way toselect areas of interest of an image, while ignoring the parts we are not concerned with.

9. Edge detection by Laplacian filter.

10. The negative of the image that’s used to make positive prints on photographic paper by projecting the negative onto the paper with a photographic enlarger or making a contact print. The paper is also darkened in proportion to its exposure to light, so a second reversal results which restores light and dark to their normal order.

The purpose of this application is to enhance the raw images captured by Juno’s Cam that were subjected to noise, blurring and other imperfections to deliver the best visualizing experience for the public outreach, scientific and artistic communities by the means of the application features enabling the user to manipulate the image by these features and experience different views so from this we can conclude that the benefits of the application are mainly

1. Offering the user, the best user experience possible as the UI is user friendly.

2. Providing the user with a diverse range of image processing features to manipulate the image in the desired way.

3. Enabling the user to share his output work in a community with similar interests through easy social media accessing without leaving the application!

4. Enabling the user to download any image captured by Juno’s Cam from NASA’s official website through simple URL entry.

5. Entitling the user to recognize the difference between the raw and processed image through comparing between both side to side which stemmed from the image’s allocation in the GUI.

The application is installed through its execution file as the application is a desktop application, A Graphical user interface appears to the user that composed of a button to upload the image as a method and a textbox to enter the image URL from NASA’s official website as other option, after selection of the image the user gets to choose which feature to apply on the image from the application’s features and see the raw inputted image and the processed image next to it in addition to its histogram. After that the user can share the processed image through different social media platforms that include Facebook, Instagram, Twitter, and LinkedIn.

The innovation in the application haven’t stopped at this limit, considering the artistic communities limit, we implemented artistic filters that helps widen the insights of the users to the Jovian system through diverse filters highlighting hidden details of the Jovian system.

As for future work, it’s represented in 4 areas which are:

1. Applying Artificial intelligence in the application in art area by auto creating artistic images of the Jovian system and GIF creation.

2. Applying Artificial intelligence to auto process the image according to its needs to ensure the best processing done on the image.

3. Converting the desktop application into a web based one to facilitate the usage even more as to ensure no user has technical issue with the installation.

4. Converting the desktop application into mobile application to ensure its usability even more.

The project depended on PyCharm as software (IDE), Python as programming language and the designs of the UI and presentation were illustrator based.

Space Agency Data

The project uses the raw images taken by the JunoCam by downloading it from the official Nasa website to process them. In the future, it will also use the images taken by JUCIY, JEO, and JGO which are satellites that are scheduled to orbit around the Jovian system and get its images, those images are important for us because in JEO, which is an orbiter around Jupiter's moon (Europa), case scientists believe that there is an enormous ocean which exists under its icy crust which means that there is life beyond Earth. So, we need to get those images taken by the JEO camera and process them to know the truth from Earth.

The raw images that we get from the satellites are processed through the application to get at the end processed photos that are scientific and artistic. If there is a problem in the raw images such as bad contrast, Not RBG, law quality, etc.; the application will enhance and overcome those problems.

Space outreaching for the public is a neglected topic that requires a lot of awareness and can be solved by studying it and its effects on earth. So, enlightening the average person about its importance and drawing them into is a necessity.

Hackathon Journey

The hackathon experience for me and my team was so inspiring on both technical and personal levels. We got to have multiple discussions with various mentors and were able to receive not only their advice and feedback, but we were also able to build a network of people with same interests and fields from various ages and experience levels which was so promising for us.

We learnt on a technical level multiple discipline and approaches regarding art creation in image processing and for the personal level, we have benefited from the mentors and their experience specially how to pitch your idea.

The main reason that inspired my team to choose this challenge is that it outreaches the public through scientific and artistic way.

My team learnt to resolve setbacks faced by cooperation between all the team members and coordination of the tasks distribution as each task was assigned to whom would do the best of it.

As a result of this cooperation, coordination, discipline and hardworking, the final output was able to rise to our level of expectations reaching efficiency, creativity, and highest validity.

We want to genuinely thank the mentors and event organizers for their endless efforts and guidance.

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