When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works.

Samsung announces the world's first 0.7μm-pixel mobile image sensor

Samsung Electronics has been pushing the envelope of mobile image sensors for a while now. Today, the Korean giant took it a step ahead and introduced the 43.7-megapixel (MP) Samsung ISOCELL Slim GH1, which is the world's first 0.7-micrometer (μm)-pixel image sensor.

What that basically means is that the sensor packs around 43.7 million pixels, each measuring 0.7μm across, in a package that the manufacturer believes is compact enough for today's thin, bezel-less phones.

The ISOCELL Slim GH1 boasts ISOCELL Plus, which is Samsung's latest pixel isolation technology that helps capture sufficient light and color information to produce more detailed and vivid pictures while minimizing optical loss and color cross-talk. In low-light situations, a place where smartphone cameras have more or less struggled in the past courtesy of small sensor-sizes, the Slim GH1 makes use of Tetracell, which is a pixel-merging technology that enables higher light sensitivity equivalent to that of a 1.4μm-pixel image sensor. This should, at least on paper, improve low-light photography on smartphones employing the Slim GH1.

The 0.7μm sensor also supports electronic image stabilization (EIS) and Super PD, which is the Korean giant's phase-detection auto-focus technology that will allow stable, fast and accurate autofocus while shooting photos and videos. Samsung is also claiming that the Slim GH1 will allow more detailed backgrounds, especially in high-resolution, 60 frames-per-second 4K videos, by employing the same Tetracell technology whereby the image sensor's resolution of 7968 × 5480 will be scaled down to 3984 × 2740, providing a greater field of view on 4K resolution (3840 x 2160).

Furthermore, the sensor is expected to be in mass-production by the end of this year.

Report a problem with article
Next Article

Samsung Galaxy S10 series updated with Note10's Link to Windows feature and more

Previous Article

Deep learning has now been used for the first time to study dark matter

Join the conversation!

Login or Sign Up to read and post a comment.

0 Comments - Add comment