Image Smoother
A easy-tier problem at 68% community acceptance, tagged with Array, Matrix. Reported in interviews at Toptal and 3 others.
Image Smoother is an easy-rated matrix problem that appears in interviews at Toptal, Verkada, Visa, and Roblox. You're given a 2D array representing pixel values and need to smooth it by replacing each pixel with the average of itself and its neighbors. The acceptance rate sits at 68 percent, which means most who attempt it pass, but there's still a meaningful miss rate. The trap is overthinking the boundary conditions. If this one hits your live assessment and you blank on the neighbor-averaging logic, StealthCoder reads the problem off your screen and surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Image Smoother"
Image Smoother is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core pattern is iterating over every cell and computing the average of all valid neighbors (including the cell itself). The catch: you have to handle edges and corners correctly without double-counting or going out of bounds. A straightforward nested loop with a bounds check solves it, but some candidates overcomplicate it with extra data structures or nested helper functions when a single pass with careful indexing works fine. The problem tests whether you can translate a visual algorithm into clean boundary logic, not graph theory or dynamic programming. This is a warm-up problem that screens for basic matrix navigation. StealthCoder is your hedge if the boundary logic trips you up during the timed assessment and you need the pattern confirmed instantly.
Pattern tags
You know the problem.
Make sure you actually pass it.
Image Smoother recycles across companies for a reason. It's easy-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Image Smoother interview FAQ
Is Image Smoother actually asked at big tech companies?+
Yes. It's confirmed at Toptal, Verkada, Visa, and Roblox. It's not common at core FAANG but appears regularly in financial services and design-tool interviews. The 68 percent acceptance rate shows it's a legitimate screening problem, not a toy.
What's the trick people miss?+
Boundary handling. Candidates often hardcode neighbor offsets and forget to skip out-of-bounds indices, or they double-count a pixel. The correct approach: iterate all nine possible neighbor positions, but only average those that exist. A simple bounds check prevents the crash.
Can I solve this without extra space?+
You need to store the smoothed values somewhere, so you can't modify the input in-place and read from it simultaneously. Most solutions use a new 2D array. If space is flagged as a constraint, some interviewers accept output to a new array; read your problem statement carefully.
How does Image Smoother relate to Array and Matrix topics?+
It's a pure matrix traversal problem. You're working with a 2D array, iterating over rows and columns, and accessing neighbors via index arithmetic. No special data structures or algorithms required, just solid 2D array indexing.
Is this problem worth drilling if I'm targeting Visa or Toptal?+
Yes. It's explicitly on their interview list and signals comfort with matrix navigation. The 68 percent pass rate means it's still a filter. Spend 15 minutes understanding the boundary logic, then move on to harder problems.
Want the actual problem statement? View "Image Smoother" on LeetCode →