Google Nexus 6P review: Serious contender for mobile photography | DxOMark
Today Google unveiled the Nexus 6P. Having partnered with manufacturer Huawei to build this latest device, the Nexus 6P is the first to run Google’s most up-to-date version of its Android operating system — Android OS 6.0 Marshmallow (or “Android M”).Tech specs for the Nexus 6P include a large 5.7-inch (1440 x 2560-pixel) AMOLED screen with Corning Gorilla Glass 4 and 16 million colors. The rear camera offers a 13Mp resolution on a 1/2.3”-type se…
It seems compact enough to be in your pocket when you'll get out: more than Sony QX smart lenses although at the expense of a zoom lens.
+DxO is being dishonest by using the DSLR comparison we read too often: "The power of a DSLR" They argue that the DXOMark sensor score is "Up to 85" which is slightly higher than as a last-gen Sony 1.5x crop APS-C sensor, despite the DxO One use a Sony 1" sensor.
Actually this is is a theoretical score calculated by using computational photography blending multiple exposures, comparing apple and oranges. So.. yeah, there's that.
It's good to see new cameras implementing computational photography methods however, including for RAW!
The website announce 650€ to pre-order it, then tell me it will be available only in the US for now (I'm in France)
– Both lack flat-field correction – Both provide incomplete matrix-only color profiling: no DCP – Neither use compression – HTC One M9 DNG is 10 bit stored in 16bit uncompressed data: 39MB per 20 Mpixel image. – LG G4 DNG is 10 bit stored uncompressed, 20MB per 16 Mpixel image – Both have non-optimal noise profiling settings: HTC One M9 set noise reduction too high and LG G4 lacks noise profiling entierly.
Notes on flat-field correction: Mobile camera modules require such correction to correct both vignetting and color cast (like pink spot / greenish or blueish corners). HTC One M9 requires less correction than the LG G4. It is only possible to compensate for light fall-off, in RAW image editors, not color cast. As a result, the color cast in corners is essentially non-fixable.
Attached: the #LGG4 DNG sample provided by +Colby Brown rendered in Lightroom with only modification an increased contrast and exposure slightly, to make both vignetting and color cast more obvious.
The least I can say is that there's room for improvement, both DNG implementation being non-optimized and incomplete.
Android Camera2 API promises to revolution digital imaging on smartphones or altogether with advanced capture and processing capabilities that have never been accessible to third party applications before.
Some of what becomes possible is manual controls, computational photography, RAW #DNG capture, full control over video recording, custom image processing. Limits are few.
Here's an analysis on how much of this new API is supported by the #Lollipop devices released during #MWC15 , including the highly anticipated Samsung Galaxy S6 and HTC One M9 flagships.
This starts a collaboration with the good people at +FrAndroid.
It's about Lollipop, Camera2 API and its 3 main levels of hardware support. The new Android OS came with a lot of promises in photo and video capabilities, but we don't know yet if they'll be fulfilled.
+Tek Syndicate just published one in video and they're pretty enthusiasts about the results 🙂
A tip about converter software: +Albert Manduca, who shows his experience with RAW editing uses +Adobe Lightroom which is great as it's one of the software that implement all the DNG capabilities I used during profiling. Mainly: * Color calibration * Noise profiling * Lens vignetting correction and sensor color uniformity
DNG files are the RAW sensor data plus metadata that describe shooting conditions and how to transform what the sensor sees into a corrected image representing colors as they are. Compared to proprietary RAW formats, DNG is self-describing.
Smartphones' captures require more correction than other cameras due to their physical constrains. Some converters support DNG but not all its features. Typically, noise, vignette or color uniformity won't be corrected as expected, color conversion incomplete, exposure compensation not applied so be sure to use a fully fledged RAW editor!
By the way, did anyone made a comparison with a Lumia DNG?
No automatic metering nor white balance is gonna provide perfect result in every situation.
I don't think +Tom's Guide calling this "a big problem" is particularly fair in this article.
Their video demonstration of white balance shifting when the scene changes (hand introduced and removed from the scene) is at best inconclusive, that's pretty much the expected behavior. If you want to know the reason why fixed or manual white balance is sometimes required, well that's it 🙂 Maybe the white balance adjustment could be slower, which would make it less apparent, but that would reduce its efficiency in other scenes with mixed lighting conditions.
Also, this sentence shows the author doesn't get how automatic white balance works, by stating the exact opposite of the reality: In reviewing some of our test photos, Apple representatives said that the colors may have shifted as the result of changing content in different photos. But that's not how white balance works. It takes account of the color of light falling on the subjects, not on the assortment of subjects in a photo
Everything an AWB algorithm has to work with is the raw pixels values from the sensor, and some knowledge of what was going on before. It doesn't know anything about light sources, weather conditions, light reflections.
In my last post, I was talking about flat field correction, a technique that allows to fix lens vignetting and associated lens+sensor color cast.
Here's a first result 🙂
This is the same picture of an uniform white reference, with contrast +100 in Lighroom to emphasis the difference:
– Without DNG correction – Without DNG correction but with Lighroom built-in Lens Vignetting tool adjusted to best settings possible – With DNG flat-field correction defined in the DNG file itself: to the user, it's like vignetting or color cast were never here!