Ricoh Launches Pentax KP Weatherproof DSLR With Extreme Low-Light Shooting Capability

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By Roydon Cerejo | Updated: 27 January 2017 13:49 IST
Highlights
  • The camera supports a high sensitivity of up to ISO 819200
  • It’s an APS-C sensor with support for DA-series lenses
  • The Pentax KP is arriving on February 25 for $1,100

Ricoh Imaging has launched the Pentax KP, a compact and portable APS-DSLR, designed specifically for night photography. The camera will go on sale from February 25 for $1,100 (approximately Rs. 74,800). The highlight feature here is the very high sensitivity of the sensor which goes all the way up to ISO 819200, which should make it possible to capture images in next to no light.

The Pentax KP features a 24-megapixel APS-C sensor with a 27-point autofocus system and is the first Pentax APS-C camera to have the Shake Reduction II system with is essentially a 5-axis image stabilisation system. The KP’s rugged exterior is dustproof and weather-sealed and can withstand temperatures as low as -10 degrees Celsius. Some proprietary Pentax technologies include Pixel Shift Resolution, which is said to offer more accurate colour reproduction and an anti-aliasing filter simulator to reduce moiré effect just like as optical filter.

“We designed the Pentax KP to appeal to the world’s most discerning outdoor photographers, who will appreciate its rich and powerful feature set and rugged, compact design, whether they are shooting a landscape on a trek in Patagonia or capturing an eclipse,” said Kaz Eguchi, president, Ricoh Imaging Americas. “From Pixel Shift Resolution to our new generation of Shake Reduction, Pentax proudly continues to lead the way in photographer-friendly innovation.”

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Other features include an electronic shutter speed of 1/24000 second; burst shooting of 7fps; 1080p video recording; vertical-tilt 3-inch LCD display, built-in Wi-Fi, and compatibility with Pextax’s DA-series lenses. The KP also features a real-time scene analysis system that’ supposed to analyses factors like brightness distribution in the image field and the subject’s primary colour and motion. It then uses deep learning technology to assess the scene more accurately and sets the appropriate exposure setting.

 

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