Posts Tagged ‘16:9’

A Future Development of Open Source Content-Aware (Moving) Image Editing Software?

June 11, 2014
content aware digital video remaster

A sample digital video image dimension conversion from conventional 4:3 to 16:9 aspect ratio without cropping using a future open source programming of content-aware to recover a missing detail. (Video clip from Facebook page via YouTube of Be Careful With My Heart thru, used with permision.)

For the  past few years we had often enjoy to watch a conventional moving image dimension—whether on film or TV or video—with an aspect ratio of 4:3. But on today’s digital age, when 16:9 digital video image was introduced in DTV broadcasting, Internet streaming, and  digital home video system, someone had requested to remaster digitally from 4:3 image to a true content-aware 16:9 image without cropping but rather recovering a missing detail from being pillar box layout. One of the recent example of fully-licensed commercial software was Adobe Photoshop CS5, which is capable to recover a missing detail of original 4:3 still image while lying under 16:9 image master layout. However, the use of commercial software would be very expensive as well as labor cost to process for a long time to remaster the entire sample old moving image dimension. To solve this problem, my only wish is to develop an open-source software based on Linux OS and GNU technology using an affordable calculation of MPEG-based or JPEG-based image recovery value constant, relative to a conventional mathematical constant such as pi (π) equal to 3.14… Although I’m not a computer programmer, here is my own suggestion to the developer of open-source imaging software such as GIMP as well as community:

  1. Take a sample of high resolution, wider aspect ratio, digital still image from a standard high performance digital camera. Suppose, for example, a high quality 4K resolution (2160p) with an aspect ratio of 16:9.
  2. While preserving an original sample image capture, copy the image and then:
    a. Crop the original 16:9 image dimension to 4:3 image dimension. To find the width for converting  4:3 image from 16:9 image, the following equation is as follows:
    Width (in pixels) (4:3) = Length (in pixels) × (4 ÷ 3)
    b. Reduce the original high resolution image being cropped from step 2a to become a standard definition (SD) nominal image resolution, such as 480p (720 × 480) or 576p (720 × 576).
  3. Using a system based from MPEG or JPEG format, calculate to find a constant value between SD resolution and high resolution image of the same aspect ratio image dimension given in step 2b, and find a constant value between 4:3 image and 16:9 image given from step 2a. The following respective equation is as follows:
    a. Original low resolution image of the same imaging object  (Rl) ÷ Original high resolution image of the same imaging object (Rh) = True content-aware high resolution image conversion constant (Khrc) [Rl ÷ Rh = Khrc]
    b. Original 4:3 short aspect ratio image of the same imaging object (Ps)÷ Original 16:9 long aspect ratio image of the same imaging object (Pl)= True content-aware wide aspect ratio image dimension conversion constant (Kwarc) [Ps ÷ Pl = Kwarc]
  4. Repeat steps 1, 2, and 3 to make another respective sample constant value of image aspect ratio and image resolution true content-aware conversion calculation.
  5. To test whether the use of respective conversion constant value of image resolution and image aspect ratio based from MPEG or JPEG would work as a true content-aware open source system, take a sample image being scanned in low resolution and limited aspect ratio dimension. Hence:
    a. Revealing a true content-aware high resolution image detail [Rh = Rl × Khrc (vary)]
    b. Revealing a true content-aware wide aspect ratio image dimension [Pl = Ps × Kwarc (vary)]

Whether the use of open-source based system would work as mentioned above or not in order to surpass the current commercial image editing software to function content-aware image remaster system, the most important thing is to have a thorough study to produce a new system and would take a long time to process with the cooperation of a fellow well-trained open-source software programmer. If this would be a reality, then various commercial film or TV producer would never have to worry to pay more to remaster old film or TV video content at an affordable processing cost.