{"id":89847,"date":"2026-02-15T11:09:29","date_gmt":"2026-02-15T14:09:29","guid":{"rendered":"https:\/\/tech.einnews.com\/article\/892561004"},"modified":"2026-02-15T11:09:29","modified_gmt":"2026-02-15T14:09:29","slug":"your-next-phone-needs-this-new-tech-to-stop-it-ruining-your-sunset-photos","status":"publish","type":"post","link":"https:\/\/new7.shop\/zerocostfreehost\/index.php\/2026\/02\/15\/your-next-phone-needs-this-new-tech-to-stop-it-ruining-your-sunset-photos\/","title":{"rendered":"Your next phone needs this new tech to stop it ruining your sunset photos"},"content":{"rendered":"
\n
\"realme<\/p>\n
\n

Hadlee Simons \/ Android Authority<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n

Whether you\u2019re snapping a family portrait or capturing the city at night, today\u2019s best smartphone cameras are undoubtedly brilliant<\/a>. Computational photography, multi-lens systems, and ever-larger sensors have pushed image quality to levels that would\u2019ve seemed impossible at the start of the decade. But while most of the attention goes to new software tricks<\/a> and megapixel counts, some of the most meaningful improvements are happening deeper in the camera stack, helping smaller mobile sensors catch up with larger mirrorless cameras.<\/p>\n<\/div>\n

\n

If you\u2019ve been reading through camera spec sheets lately, you might have spotted the term LOFIC appear next to some of the industry\u2019s latest high-end camera sensors. Namely, on the Xiaomi 17 Ultra<\/a> and HUAWEI Pura 80 Ultra<\/a>, two powerhouse mobile camera setups. These phones already boast serious camera credentials, but LOFIC isn\u2019t about flashy features or AI processing. Instead, it\u2019s a fundamental change in how sensors handle light.<\/p>\n<\/div>\n

\n

The acronym might not mean much at first glance, but LOFIC represents a clever hardware solution to one of photography\u2019s oldest problems: capturing both bright highlights and deep shadows in a single exposure. To understand why that matters \u2014 and why it\u2019s such a big deal for mobile cameras \u2014 we need to start with how an image sensor actually captures light.<\/p>\n<\/div>\n

What is LOFIC?<\/h2>\n<\/p>\n
\n
\"fairphone<\/p>\n
\n

Rita El Khoury \/ Android Authority<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n

LOFIC stands for Lateral Overflow Integration Capacitor, which, surprisingly, hints at what\u2019s going on here. But before we get to that, here\u2019s a really quick primer on how an image sensor actually captures light.<\/p>\n<\/div>\n

\n

At its most basic level, your phone\u2019s camera sensor consists of small pixels. Inside those pixels is a color filter and a photodiode that charges a capacitor (also sometimes called a well) whenever a photon reaches it. Once a photo\u2019s exposure is complete after pressing the shutter, we measure the capacitor\u2019s voltage as an analog signal to determine how much light reached that specific pixel \u2014 and all the other pixels across the sensor (giving us variations in light and dark). We apply a predetermined amplifier value (ISO) to scale the sensor\u2019s voltage outputs, mapping dark and bright areas into a usable range. Choosing the right ISO is often where the trade-off between bright highlights and shadow detail comes into play.<\/p>\n<\/div>\n

\n

Hopefully, you can see a potential problem here. Too low a gain value risks underexposure and dark values that are all crushed together, while very high gain risks clipping our maximum value. This imposes a rather difficult limit on the dynamic range we can capture in a single exposure; it\u2019s very difficult for a single gain value to expose light and dark perfectly, especially on small sensors. Instead, phone cameras often resort to clever tricks to combine multiple exposures, such as Google\u2019s famous software HDR algorithm or on-sensor dual-ISO gain techniques.<\/p>\n<\/div>\n

\n
\"LOFIC<\/div>\n<\/div>\n
\n

LOFIC takes a different approach by adding extra overflow capacitor wells to the image sensor. You can think of the capacitors as cascaded buckets that can overflow and catch excess charge when the previous photodiode reaches its limit. Once the smaller, more sensitive bucket for low-light conditions fills up, a second bucket continues to capture photon charge in bright areas. Now, when we read values from the buckets, we can use different gain values for each, such as high gain for a shadow-detail bucket and lower gain for highlights, reducing the risk of clipping highlights and thereby extending the sensor\u2019s dynamic range.<\/p>\n<\/div>\n

LOFIC lets pixels capture accurate highlights and shadows simultaneously.<\/q><\/p>\n

\n

This is a bit of an oversimplification, as modern image sensors also use capacitor wells for features like Phase Detection AutoFocus and gain selection too, and there are plenty of other factors that go into making a top-quality sensor. Still, the general premise is sound. By splitting raw light-capture information into multiple levels, signal gain can be optimized, increasing dynamic range in a single exposure without relying on software trickery.<\/p>\n<\/div>\n

How LOFIC actually improves your photos<\/h2>\n<\/p>\n
\n
\"Pura<\/p>\n
\n

Paul Jones \/ Android Authority<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n

Even if the inner workings of LOFIC feel a bit abstract, its goal is simple: capture more of a scene\u2019s real-world contrast in a single shot. That means preserving bright highlights without sacrificing shadow detail \u2014 something that\u2019s especially challenging for smaller smartphone sensors.<\/p>\n<\/div>\n

\n

Traditionally, phones tackle this problem with software HDR, which captures and stacks multiple exposure frames. While effective, this approach struggles with motion, often introducing ghosting, halos, or blurred detail when subjects move between frames (though high-end algorithms can assist with this). Modern dual-ISO (or dual conversion gain \u2014 DCG) sensors offer a more robust hardware-based alternative by reading the same exposure at two different gain levels and merging the results. This improves sensitivity and dynamic range while avoiding motion artifacts in a pretty cost-effective setup. However, this hardware is typically limited to two gain stages and seldom operates per-pixel.<\/p>\n\n\n\n\n\n\n\n\n\n
Feature<\/th>\nSoftware HDR<\/th>\nDual-ISO<\/th>\nLOFIC<\/th>\n<\/tr>\n<\/thead>\n
Motion handling<\/td>\nModerate<\/td>\nExcellent<\/td>\nExcellent<\/td>\n<\/tr>\n
Highlight retention<\/td>\nGood<\/td>\nGood<\/td>\nExcellent<\/td>\n<\/tr>\n
Shadow detail<\/td>\nModerate<\/td>\nGood<\/td>\nExcellent<\/td>\n<\/tr>\n
Noise in dark areas<\/td>\nModerate<\/td>\nLow<\/td>\nVery low<\/td>\n<\/tr>\n
Single exposure?<\/td>\nNo<\/td>\nYes<\/td>\nYes<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

LOFIC takes a different approach by actually changing the sensor\u2019s ability to measure light. Instead of relying on a single charge well \u2014 or even just two gain readouts \u2014 LOFIC-equipped pixels use additional overflow capacitors to catch excess charge from bright areas. The result is smoother highlight roll-off, reduced clipping in bright regions, and cleaner shadow detail with lower noise. Because the extra charge is stored before readout, the sensor can apply optimal gain levels to different brightness ranges without amplifying noise or blowing out highlights. In high-contrast scenes, this means less reliance on aggressive tone mapping and fewer HDR artifacts, but it comes at the cost of more complex and therefore more expensive sensor manufacturing.<\/p>\n<\/div>\n

\n

I\u2019m loath to put exact numbers to any of these technologies, because variations in sensor design and processor support can significantly affect the results. Broadly speaking, smartphones using traditional HDR approaches tend to achieve around 60\u201390 dB of effective dynamic range, depending on the sensor and the software or hardware HDR method employed. By contrast, OmniVision\u2019s 1-inch OV50X sensor, using DCG and LOFIC, is specified at close to 110 dB of dynamic range at the sensor level \u2014 a substantial increase, even if the comparison involves more nuance than raw numbers alone.<\/p>\n<\/div>\n

\n
\"ov50x<\/p>\n
\n

Omnivision<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n

In practical terms, imagine shooting a silhouetted cityscape against a bright sunset. A conventional or even a dual-gain sensor may render the sun and surrounding clouds as flat, blown-out, white shapes, or crush shadow detail into darkness. With LOFIC, the sensor can retain color and gradient in the brightest parts of the sky while still lifting detail from the shadows below. The same principle applies to night cityscapes, where bright streetlights and deep shadowed alleys can coexist without one overwhelming the other.<\/p>\n<\/div>\n

\n

Because LOFIC operates entirely in hardware and works on a per-frame basis, its benefits also extend to video. Each frame carries a wider dynamic range, helping preserve natural colors, avoid blown highlights, and maintain detail in shadows \u2014 even in challenging lighting \u2014 without the need for multi-frame processing.<\/p>\n<\/div>\n