Clicks and clipping — repairing damaged samples

The last two chapters reduced unwanted sound that sat alongside the good stuff. This chapter is different: here the good sound has been destroyed in places, and the tool has to rebuild it. These are the “repairer” tools from chapter 3, and they behave more like an art restorer repainting a damaged canvas than like a filter.

Clicks — tiny holes in the wave

A click is a brief, violent spike: a speck of dust on a vinyl record, a scratch, or a sloppy digital edit that left a sudden jump. On the waveform it’s a single sample (or a few) shooting way out of line with its neighbours; on the spectrogram it’s a thin vertical streak, because an instantaneous spike contains a flash of every pitch at once.

The fix, de-click, is wonderfully intuitive:

1. Find the spike. Compare each sample to the typical level of its neighbours. If one is wildly larger than the local average — say ten times — it’s almost certainly a click, not real sound. (Cathar’s --threshold is exactly this “how many times louder than normal counts as a click” number.)
2. Cut it out and redraw. Delete the offending samples, leaving a tiny gap, and draw a smooth curve across the hole that connects what came before to what comes after. Cathar uses a gentle curved line (a cubic interpolation) so the patch blends in.

Because a click is only a handful of samples — a fraction of a millisecond — the gap is tiny and the redraw is almost always invisible. De-click is one of restoration’s reliable wins.

Clipping — when the tops get chopped off

Clipping is nastier. Every recording system has a ceiling: the loudest it can represent (that ±1.0 from chapter 1). Push a signal past the ceiling — record too hot, overdrive a preamp — and the system can’t go higher, so it just flattens the peak off. The rounded tops of the wave become flat plateaus. You hear it as a harsh, fuzzy, “broken speaker” distortion on the loud parts.

  recorded fine:                 CLIPPED (overloaded):
                                 ceiling ┄┄┏━━━━━┓┄┄  ← the top is chopped flat;
        ╭───╮                            ┃     ┃        the real curve is GONE
       ╱     ╲                          ╱       ╲
     ─╯       ╰─                      ─╯         ╰─

  de-clip's job: guess the missing dotted peak from the slopes either side
                                 ┄┄┄╭╴╴╮┄┄┄  ← an invented, plausible curve
                                  ╱      ╲     (a guess, not a recovery)
                                ─╯        ╰─

Here’s the cruel part: when the top is flattened, the information about how high the wave really wanted to go is gone. Unlike a click (a brief spike you can delete), clipping erases whole stretches of the true waveform and leaves a flat line where a curve should be. De-clip has to guess the missing peak from the shape of the wave on either side.

How do you guess a peak you can’t see? You use the fact that real sound is predictable: the wiggle approaching the flat top was on a clear trajectory, and the part leaving it continues that trajectory, so you can extrapolate the curve that “should” have been there — rising above the ceiling and coming back down — instead of leaving a plateau. The better the prediction model, the more natural the rebuilt peak.

An honest word about de-clip

De-clip is the hardest tool in this book, and it’s important to set expectations:

• A lightly clipped recording (a few peaks just kissing the ceiling) cleans up beautifully — there’s lots of surrounding curve to predict from, and the gaps are short.
• A badly clipped recording (long flat stretches, a distorted scream) can be softened but never truly restored. The original is gone; the tool is inventing, and across a long flat run even a clever guess drifts. Expect “less harsh,” not “as if it never happened.”

The professional state of the art here is genuinely sophisticated — it treats the missing samples as unknowns and solves for the values that best fit a model of the surrounding sound (an “autoregressive” prediction, the classic method) or that make the result as simple as possible in the frequency view (a modern “sparse reconstruction” approach). These are real mathematics, not a smooth line across the gap, and they’re why a top declipper can rebuild a peak so convincingly.

How the big tools do it

• Audacity has a “Clip Fix” effect that estimates the missing peaks from the surrounding slope — the same basic idea as a simple de-clip.
• Adobe Audition’s “DeClipper” and the click-focused “Automatic Click Remover” handle both problems with adjustable thresholds.
• iZotope RX is, again, the benchmark. Its “De-clip” and “De-click” modules use the advanced prediction/reconstruction methods above and apply them automatically across a whole file; “De-crackle” extends de-click to the dense, continuous crackle of old records. For serious restoration of damaged vinyl or badly clipped masters, RX is the tool the pros reach for.

Cathar’s de-click is solid and reliable, and its de-clip uses the modern “sparse reconstruction” method described above — A-SPADE (Kitić, Bertin & Gribonval, 2015), the same family iZotope-class tools use. It treats the clipped samples as unknowns and solves for the signal that is simplest in the frequency view (sparsest across a windowed, overlapping spectrum) while keeping every reliable sample exact and every clipped sample beyond the threshold — so a peak is rebuilt toward its true height rather than flattened to a plateau. It’s an iterative solve (a little slower than a one-shot fill, and worth it). Light-to- moderate clipping cleans up convincingly; it’s still not a substitute for RX on heavily distorted material — across long flat runs any tool is guessing. As always: knowing how badly something is damaged tells you whether any tool can save it.