Fujifilm XT1
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Written by Gordon Laing
Fujifilm XT1 vs Olympus OMD EM1 Noise JPEG
 To compare noise levels under real-life conditions, I shot this scene with the Fujifilm XT1 and Olympus OMD EM1 within a few moments of each other using their RAW+JPEG settings at each of their ISO sensitivity settings. On this page I’m comparing their JPEG quality. In my first noise comparison the XT1 was fitted with the Zeiss Touit 32mm f1.8 and the OMD EM1 fitted with the Leica 25mm f1.4, both set to f8 in Aperture Priority mode. Due to the crop factors on their sensors, both cameras delivered the same field of view. I have a second noise comparison lower on the page using the kit zooms. Note the Fujifilm 35mm f1.4 was unavailable either from Fujifilm or local rental firms at the time of testing. For my noise results I fitted the Fujifilm X-T1 and Olympus OMD EM1 with prime lenses which deliver a similar field of view once their sensors have been taken into account. For the X-T1 I used the Zeiss Touit 32mm f1.8 and for the EM1 I used the Leica 25mm f1.4. I wanted to use the Fujifilm 35mm f1.4 as it’s similarly priced to the Leica 25mm f1.4, not to mention sharing the same aperture and supporting the X-T1’s Lens Modulation Optimiser, but Fujifilm was unable to send me one for testing and no UK hire firms had one available at the time of testing. So I used the Touit instead, which I rented from UK firm, hireacamera. I intend to repeat this test in the future with the Fujifilm 35mm f1.4. Note the Touit is a more expensive lens than the Leica 25mm, by around 50%. At first glance here I feel the EM1 plus 25mm f 1.4 is delivering a slightly crisper result than the X-T1 plus Zeiss Touit 32mm f1.8, although both combinations are recording essentially the same degree of spatial detail. As you proceed through the ISO range, keep an eye not just on the fine details and background noise, but also the tonal dynamic range in the rose petals. With the subject cropped below I’d say both cameras share similar degrees of noise and spatial resolution up to 800 ISO for JPEGs, although as the sensitivity increases from the base of 200 ISO to 800 ISO the EM1 gradually loses tonal highlight detail in some of the rose petals. This could be an issue for wedding photographers in particular, although you could of course adjust the highlight curve on the EM1 to compensate. Either way with the default settings the X-T1 clearly has more tonal headroom for highlights. At 1600 and 3200 ISO the EM1 begins to exhibit more noise than the X-T1, and subtle tonal details are becoming mushy. At 6400 ISO the EM1’s noise reduction becomes more aggressive, smudging a lot of finer details that remain fairly crisp on the X-T1. At 12800 ISO both camera’s JPEGs suffer from a lot of visible noise, but the X-T1 is holding onto finer spatial and tonal detail. At 25600 ISO both look horrible and I didn’t bother to test the X-T1’s highest 51200 ISO setting. From this page of in-camera JPEG comparisons it’s clear the Fujifilm X-T1 enjoys an advantage in noise levels above 800 ISO, but also records more highlight detail with the default settings throughout almost the entire range. This is to be expected from its bigger sensor and is a key advantage it enjoys over the Micro Four Thirds format. But how much of what you’re seeing below is down to in-camera processing? To find out I processed RAW files using exactly the same settings and you can see the results in my Fujifilm XT1 RAW noise results. Just before moving on though, you may enjoy an additional noise comparison below the first table, showing crops from spirits bottles. I made this early during my tests using each camera’s respective kit zooms, and the crop from the edge does the EM1 no favours due to the 12-50mm’s optical quality. But if you can look beyond the sharpness of details and concentrate on the noise levels in areas of flat colour, I think the difference in noise is very clear to see. Now onto my Fujifilm XT1 RAW noise results, or perhaps you’re ready for my Fujifilm XT1 sample images or can’t wait to skip straight to my verdict!
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