Tuesday , January 26 2021

Scientists translate the image of sunset into music



Using photo 5.000. the sunrise on Mars, caught in NASA's Rever Opportunity, British scientists have created a two-part piece of music.

The soundtrack was created by scanning the image from left to right, pixel by pixel, and viewing brightness and color information and combining them with the height of the terrain.

The team used a technique called "data simulation" that implemented computer algorithms to make each element determine a certain slope and melody to translate a photo into music.

"We are absolutely delighted in presenting this work on such a fascinating planet," said Domenico Vicinanza, head of the Sound and Game Engineering (SAGE) research team at Anglia Ruskin.

"Image synchronization is truly a flexible technology for science research and can be used in several domains, from studying certain characteristics of planetary surfaces and atmospheres, analyzing weather patterns or detecting volcanic eruptions," adds Vicinanza.

Quiet and slow harmony is the result of dark backgrounds, and lighter, higher sounds in the middle of the pieces are generated by sonifying the bright sun.

Data sonification techniques can be applied in health science to provide scientists with new methods for analyzing the appearance of certain shapes and colors, which is particularly useful in image diagnosis, the team said.

Vicinity with Genevieve Williams s University of Exeter,

will feature a piece called Mars Soundscapes at the NASA booth at the upcoming Supercomputing SC18 conference in Dallas.

It will be featured with conventional speakers and vibration converters so that the audience can feel the vibration of the hands and so enjoy the first experience of sunrise on Mars.

Opportunity is a robotic rover who has provided photographic information on Mars for NASA since 2004.

Earlier in 2018, communication stopped after dust. Scientists hope that this year will continue their work.

–IANS

rt / mag / sed

(This story has not been edited by standard business staff and is automatically generated from a syndicated feed.)


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